Online Discrimination of Nonlinear Dynamics with Switching Differential Equations

How to recognise whether an observed person walks or runs? We consider a dynamic environment where observations (e.g. the posture of a person) are caused by different dynamic processes (walking or running) which are active one at a time and which may transition from one to another at any time. For this setup, switching dynamic models have been suggested previously, mostly, for linear and nonlinear dynamics in discrete time. Motivated by basic principles of computations in the brain (dynamic, internal models) we suggest a model for switching nonlinear differential equations. The switching process in the model is implemented by a Hopfield network and we use parametric dynamic movement primitives to represent arbitrary rhythmic motions. The model generates observed dynamics by linearly interpolating the primitives weighted by the switching variables and it is constructed such that standard filtering algorithms can be applied. In two experiments with synthetic planar motion and a human motion capture data set we show that inference with the unscented Kalman filter can successfully discriminate several dynamic processes online

High temperature protective coatings for refractory metals progress report no. 1, oct. 23, 1964 - jan. 23, 1965

Iridium as high temperature protective coating for unalloyed niobium and tantalu

Safety, tolerability and pharmacokinetics of intravaginal pentamycin

BACKGROUND/AIMS: Intravaginal pentamycin is a polyene macrolide with a broad spectrum of antimicrobial activity and is effective in various forms of infectious vaginitis. We evaluated the safety, tolerability and pharmacokinetics of escalating doses of this product. METHODS: Nineteen healthy volunteers were randomized to receive double blind one of five doses of intravaginal pentamycin (3, 10, 30, 60 or 100 mg) or the corresponding dose of pentamycin vehicle daily for 6 days. Patients with symptomatic vaginitis received a single dose of 60 (n = 6) or 100 mg (n = 6) of intravaginal pentamycin. Safety and tolerability parameters were monitored throughout the study. Plasma concentrations of pentamycin were measured daily in the healthy volunteers and on the day of drug application in the patients. RESULTS: The most frequently reported adverse events were mild or moderate vaginal discharge and mild symptoms of vaginal irritation (mainly pruritus or burning sensation), which also occurred in women who applied the vehicle. No patient with symptomatic vaginitis reported treatment-related adverse events. The plasma levels of pentamycin were below the quantification limit in all samples. CONCLUSION: Intravaginal pentamycin does not cause adverse reactions compared with vehicle and is not absorbed through the intact or the inflamed vagina

Attenuated and Protease-Profile Modified Sendai Virus Vectors as a New Tool for Virotherapy of Solid Tumors

Peer reviewe

The Secret to Successful User Communities: An Analysis of Computer Associates’ User Groups

This paper provides the first large scale study that examines the impact of both individual- and group-specific factors on the benefits users obtain from their user communities. By empirically analysing 924 survey responses from individuals in 161 Computer Associates' user groups, this paper aims to identify the determinants of successful user communities. To measure success, the amount of time individual members save through having access to their user networks is used. As firms can significantly profit from successful user communities, this study proposes four key implications of the empirical results for the management of user communities

Influence of solvent granularity on the effective interaction between charged colloidal suspensions

We study the effect of solvent granularity on the effective force between two charged colloidal particles by computer simulations of the primitive model of strongly asymmetric electrolytes with an explicitly added hard sphere solvent. Apart from molecular oscillating forces for nearly touching colloids which arise from solvent and counterion layering, the counterions are attracted towards the colloidal surfaces by solvent depletion providing a simple statistical description of hydration. This, in turn, has an important influence on the effective forces for larger distances which are considerably reduced as compared to the prediction based on the primitive model. When these forces are repulsive, the long-distance behaviour can be described by an effective Yukawa pair potential with a solvent-renormalized charge. As a function of colloidal volume fraction and added salt concentration, this solvent-renormalized charge behaves qualitatively similar to that obtained via the Poisson-Boltzmann cell model but there are quantitative differences. For divalent counterions and nano-sized colloids, on the other hand, the hydration may lead to overscreened colloids with mutual attraction while the primitive model yields repulsive forces. All these new effects can be accounted for through a solvent-averaged primitive model (SPM) which is obtained from the full model by integrating out the solvent degrees of freedom. The SPM was used to access larger colloidal particles without simulating the solvent explicitly.Comment: 14 pages, 16 craphic

An Examination of Providers’ Awareness, Knowledge of Screening and Treatment, and Perceived Barriers Associated with Intimate Partner Violence-related Traumatic Brain Injury

Introduction: According to the Centers for Disease Control and Prevention, an estimated 10 million men and women are physically abused by an intimate partner. Injuries to the head, neck, and face (HNF) occur at a high rate with survivors of intimate partner violence (IPV). HNF injuries have the potential to result in traumatic brain injury (TBI) which may lead to chronic and negative physical (headaches, chronic pain, persistent vertigo) and mental health outcomes (post-traumatic stress disorder, anxiety, depression) if left untreated. Providers’ awareness of IPV-related TBI, screening tools and resources, and perceived barriers are important factors when examining IPV-related TBI. Methods: A mixed methods approach was used for data collection. The sample included providers from a variety of domains, including social work, healthcare, legal, and mental health. Three focus groups and two one-on-one interviews with providers were conducted and recorded. Prior to the focus groups and interviews, demographic data were collected via a survey. In the focus groups and interviews, providers were asked a series of open-ended questions and all audio files were transcribed and coded. Results: Several providers noted that the connection between TBI and IVP is valid and that they are more likely to screen for possible TBI in their clients following their participation in the study. Overall, providers were not aware of screening tools for TBI although some were able to name local facilities and resources. Providers noted that symptoms of TBI overlap significantly with other health conditions, which can make identification difficult. Providers discussed reservations, such as a lack of proper training, knowledge, and skills to accurately identify, diagnose and treat IPV-related TBI. Conclusion: The literature regarding IPV-related TBI is in its infancy and many aspects of this condition are still poorly understood. The results of our study support the need for an education-based intervention regarding IPV-related TBI, screening tools and available resources. Future research should examine the perceptions of TBI providers on IPV and IPV-related TBI, address the overlap of TBI symptoms with other health conditions, the efficacy of education-based interventions, and mandatory screening to increase the identification rate of IPV-related TBI

Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks

Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in standard RNN models may be an over-simplification of what real neuronal networks compute. Here, we suggest that the RNN approach may be made both neurobiologically more plausible and computationally more powerful by its fusion with Bayesian inference techniques for nonlinear dynamical systems. In this scheme, we use an RNN as a generative model of dynamic input caused by the environment, e.g. of speech or kinematics. Given this generative RNN model, we derive Bayesian update equations that can decode its output. Critically, these updates define a 'recognizing RNN' (rRNN), in which neurons compute and exchange prediction and prediction error messages. The rRNN has several desirable features that a conventional RNN does not have, for example, fast decoding of dynamic stimuli and robustness to initial conditions and noise. Furthermore, it implements a predictive coding scheme for dynamic inputs. We suggest that the Bayesian inversion of recurrent neural networks may be useful both as a model of brain function and as a machine learning tool. We illustrate the use of the rRNN by an application to the online decoding (i.e. recognition) of human kinematics