Blockade of neurotensin-induced motor activity by inhibition of protein kinase

The administration of neurotensin into the ventral tegmental area stimulates dopamine neurons and locomotor activity. Furthermore, when neurotensin is microinjected daily into the ventral tegmental area the motor stimulant response increases. The role of protein kinases in the motor stimulant effect of neurotensin was evaluated by coadministration of the protein kinase inhibitors H8 and H7 into the ventral tegmental area with neurotensin. It was found that the acute motor stimulant effect of neurotensin was abolished in a dose-dependent fashion by H8 coadministration. Neurotensin-induced activity was also blocked by H7. However, acute motor stimulation following microinjection of the mu opioid, Tyr-d-Ala-Gly-MePhe-Gly(ol) or the potassium channel antagonist apamin into the ventral tegmental area was not affected by coadministration with H8. The behavioral sensitization produced by daily neurotensin microinjection into the ventral tegmental area was also prevented by the coadministration of H8. These data indicate that the motor stimulation produced by acute and repeated neurotensin microinjection into the ventral tegmental area is dependent upon activation of protein kinase(s). Furthermore, Tyr-d-Ala-Gly-MePhe-Gly(ol) and apamine elicit locomotion independently of protein kinase(s).     

A Comprehensive Performance Evaluation of Deformable Face Tracking “In-the-Wild”

Recently, technologies such as face detection, facial landmark localisation and face recognition and verification have matured enough to provide effective and efficient solutions for imagery captured under arbitrary conditions (referred to as “in-the-wild”). This is partially attributed to the fact that comprehensive “in-the-wild” benchmarks have been developed for face detection, landmark localisation and recognition/verification. A very important technology that has not been thoroughly evaluated yet is deformable face tracking “in-the-wild”. Until now, the performance has mainly been assessed qualitatively by visually assessing the result of a deformable face tracking technology on short videos. In this paper, we perform the first, to the best of our knowledge, thorough evaluation of state-of-the-art deformable face tracking pipelines using the recently introduced 300 VW benchmark. We evaluate many different architectures focusing mainly on the task of on-line deformable face tracking. In particular, we compare the following general strategies: (a) generic face detection plus generic facial landmark localisation, (b) generic model free tracking plus generic facial landmark localisation, as well as (c) hybrid approaches using state-of-the-art face detection, model free tracking and facial landmark localisation technologies. Our evaluation reveals future avenues for further research on the topic.     

Assessment of pareto calibration, stability, and wavelength selection

Recent work has shown that ridge regression (RR) is Pareto to partial least squares (PLS) and principal component regression (PCR) when the variance indicator Euclidian norm of the regression coefficients, //p//, is plotted against the bias indicator root mean square error of calibration (RMSEC). Simplex optimization demonstrates that RR is Pareto for several other spectral data sets when //p// is used with RMSEC and the root mean square error of evaluation (RMSEE) as optimization criteria. From this investigation, it was observed that while RR is Pareto optimal, PLS and PCR harmonious models are near equivalent to harmonious RR models. Additionally, it was found that RR is Pareto robust, i.e., models formed at one temperature were then used to predict samples at another temperature. Wavelength selection is commonly performed to improve analysis results such that bias indicators RMSEC, RMSEE, root mean square error of validation, or root mean square error of cross-validation decrease using a subset of wavelengths. Just as critical to an analysis of selected wavelengths is an assessment of variance. Using wavelengths deemed optimal in a previous study, this paper reports on the variance/bias tradeoff. An approach that forms the Pareto model with a Pareto wavelength subset is suggested.     

Modeling quantum noise of phosphors used in medical X-ray imaging detectors

The noise properties of the granular phosphor screens, which are utilized in X-ray imaging detectors, are studied in terms of the quantum noise transfer function (QNTF). An analytical model, taking into account the effect of K-characteristic X-rays reabsorption within the phosphor material and the optical properties of the phosphor, was developed. The optical properties of the phosphor material required by the model were obtained from literature, except for the optical diffusion length (σ) that was determined by data fitting and was found to be 26 cm²/g. The deviation between theoretical and experimental data is σ depended. Specifically for σ=26 cm²/g and σ=25 cm²/g the respective deviations between experimental and predicted results were 0.698% and −1.597%. However for relative differences in σ more than 15% from the value 26 cm²/g, the corresponding deviations exceed by 6 times the value of 0.698%. The model was tested via comparison to experimental results obtained by a set of Y₂O₃:Eu³⁺ phosphor screens prepared by sedimentation. The model may be used to evaluate the effect of screen thickness and irradiation geometry on quantum noise of phosphor materials for transmission and reflection mode.     

Modeling quantum and structure noise of phosphors used in medical X-ray imaging detectors

The noise properties of granular phosphors used in X-ray imaging detectors are studied in terms of a noise transfer function, NTF. This study is performed in high-exposure conditions where the contribution of structure noise to total screen noise is considerable. An analytical model, based on the cascaded linear systems methodology presented in the literature, is developed. This model takes into account the quantum noise and structure noise. Furthermore, it considers the effect of the K X-rays reabsorption on the phosphor material and the effect of screen thickness on the NTF. The model was validated against experimental results obtained by a set of Zn₂SiO₄:Mn phosphor screens prepared by sedimentation. The model may be used to evaluate the effect of screen thickness and the effect of the characteristic X-rays on NTF in high-exposure conditions where structure noise is considerable.     

Tracking recurring contexts using ensemble classifiers: an application to email filtering

Concept drift constitutes a challenging problem for the machine learning and data mining community that frequently appears in real world stream classification problems. It is usually defined as the unforeseeable concept change of the target variable in a prediction task. In this paper, we focus on the problem of recurring contexts, a special sub-type of concept drift, that has not yet met the proper attention from the research community. In the case of recurring contexts, concepts may re-appear in future and thus older classification models might be beneficial for future classifications. We propose a general framework for classifying data streams by exploiting stream clustering in order to dynamically build and update an ensemble of incremental classifiers. To achieve this, a transformation function that maps batches of examples into a new conceptual representation model is proposed. The clustering algorithm is then applied in order to group batches of examples into concepts and identify recurring contexts. The ensemble is produced by creating and maintaining an incremental classifier for every concept discovered in the data stream. An experimental study is performed using (a) two new real-world concept drifting datasets from the email domain, (b) an instantiation of the proposed framework and (c) five methods for dealing with drifting concepts. Results indicate the effectiveness of the proposed representation and the suitability of the concept-specific classifiers for problems with recurring contexts.     

Conclusive local interpretation rules for random forests

Data Mining and Knowledge Discovery - In critical situations involving discrimination, gender inequality, economic damage, and even the possibility of casualties, machine learning models must be...     

Efficient reactor concepts for coupling of endothermic and exothermic reactions

Multifunctional autothermal reactors are a novel concept in process integration and intensification. They can be implemented as a countercurrent or reverse-flow reactor. A promising field of application is the coupling of endothermic and exothermic reactions. Methane steam reforming coupled with methane combustion is considered as a particular example. Several novel reactor configurations with co- and countercurrent flow in the reaction zone will be discussed by numerical simulation and an example for experimental verification will be presented.