53 resultados para single test electron model


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Single gold particles may serve as room temperature single electron memory units because of their size dependent electronic level spacing. Here, we present a proof-of-concept study by electrochemically controlled scanning probe experiments performed on tailor-made Au particles of narrow dispersity. In particular, the charge transport characteristics through chemically synthesized hexane-1-thiol and 4-pyridylbenzene-1-thiol mixed monolayer protected Au144 clusters (MPCs) by differential pulse voltammetry (DPV) and electrochemical scanning tunneling spectroscopy (EC-STS) are reported. The pyridyl groups exposed by the Au-MPCs enable their immobilization on Pt(111) substrates. By varying the humidity during their deposition, samples coated by stacks of compact monolayers of Au-MPCs or decorated with individual, laterally separated Au-MPCs are obtained. DPV experiments with stacked monolayers of Au144-MPCs and EC-STS experiments with laterally separated individual Au144-MPCs are performed both in aqueous and ionic liquid electrolytes. Lower capacitance values were observed for individual clusters compared to ensemble clusters. This trend remains the same irrespective of the composition of the electrolyte surrounding the Au144-MPC. However, the resolution of the energy level spacing of the single clusters is strongly affected by the proximity of neighboring particles.

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The XENON100 dark matter experiment uses liquid xenon in a time projection chamber (TPC) to measure xenon nuclear recoils resulting from the scattering of dark matter weakly interacting massive particles (WIMPs). In this paper, we report the observation of single-electron charge signals which are not related to WIMP interactions. These signals, which show the excellent sensitivity of the detector to small charge signals, are explained as being due to the photoionization of impurities in the liquid xenon and of the metal components inside the TPC. They are used as a unique calibration source to characterize the detector. We explain how we can infer crucial parameters for the XENON100 experiment: the secondary-scintillation gain, the extraction yield from the liquid to the gas phase and the electron drift velocity.

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The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.

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INTRODUCTION The Rondo is a single-unit cochlear implant (CI) audio processor comprising the identical components as its behind-the-ear predecessor, the Opus 2. An interchange of the Opus 2 with the Rondo leads to a shift of the microphone position toward the back of the head. This study aimed to investigate the influence of the Rondo wearing position on speech intelligibility in noise. METHODS Speech intelligibility in noise was measured in 4 spatial configurations with 12 experienced CI users using the German adaptive Oldenburg sentence test. A physical model and a numerical model were used to enable a comparison of the observations. RESULTS No statistically significant differences of the speech intelligibility were found in the situations in which the signal came from the front and the noise came from the frontal, ipsilateral, or contralateral side. The signal-to-noise ratio (SNR) was significantly better with the Opus 2 in the case with the noise presented from the back (4.4 dB, p < 0.001). The differences in the SNR were significantly worse with the Rondo processors placed further behind the ear than closer to the ear. CONCLUSION The study indicates that CI users with the receiver/stimulator implanted in positions further behind the ear are expected to have higher difficulties in noisy situations when wearing the single-unit audio processor.

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BACKGROUND: Despite long-standing calls to disseminate evidence-based treatments for generalized anxiety (GAD), modest progress has been made in the study of how such treatments should be implemented. The primary objective of this study was to test three competing strategies on how to implement a cognitive behavioral treatment (CBT) for out-patients with GAD (i.e., comparison of one compensation vs. two capitalization models). METHODS: For our three-arm, single-blinded, randomized controlled trial (implementation of CBT for GAD [IMPLEMENT]), we recruited adults with GAD using advertisements in high-circulation newspapers to participate in a 14-session cognitive behavioral treatment (Mastery of your Anxiety and Worry, MAW-packet). We randomly assigned eligible patients using a full randomization procedure (1:1:1) to three different conditions of implementation: adherence priming (compensation model), which had a systematized focus on patients' individual GAD symptoms and how to compensate for these symptoms within the MAW-packet, and resource priming and supportive resource priming (capitalization model), which had systematized focuses on patients' strengths and abilities and how these strengths can be capitalized within the same packet. In the intention-to-treat population an outcome composite of primary and secondary symptoms-related self-report questionnaires was analyzed based on a hierarchical linear growth model from intake to 6-month follow-up assessment. This trial is registered at ClinicalTrials.gov (identifier: NCT02039193) and is closed to new participants. FINDINGS: From June 2012 to Nov. 2014, from 411 participants that were screened, 57 eligible participants were recruited and randomly assigned to three conditions. Forty-nine patients (86%) provided outcome data at post-assessment (14% dropout rate). All three conditions showed a highly significant reduction of symptoms over time. However, compared with the adherence priming condition, both resource priming conditions indicated faster symptom reduction. The observer ratings of a sub-sample of recorded videos (n = 100) showed that the therapists in the resource priming conditions conducted more strength-oriented interventions in comparison with the adherence priming condition. No patients died or attempted suicide. INTERPRETATION: To our knowledge, this is the first trial that focuses on capitalization and compensation models during the implementation of one prescriptive treatment packet for GAD. We have shown that GAD related symptoms were significantly faster reduced by the resource priming conditions, although the limitations of our study included a well-educated population. If replicated, our results suggest that therapists who implement a mental health treatment for GAD might profit from a systematized focus on capitalization models. FUNDING: Swiss Science National Foundation (SNSF-Nr. PZ00P1_136937/1) awarded to CF. KEYWORDS: Cognitive behavioral therapy; Evidence-based treatment; Implementation strategies; Randomized controlled trial