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Watching soot inception via online Raman spectroscopy

In this work, online spontaneous Raman spectroscopy was applied to study the soot inception and growth zones of a low pressure premixed ethylene/oxygen flame. Firstly, we measured online Raman spectrum of aerosol soot extracted from the flame. The spectrum was compared to ex situ Raman measurements of the same soot after being deposited on a window. In the aerosol soot particles, the presence of a

A “patient-industry complex”? Investigating the financial dependency of UK patient organisations on drug company funding

We examined the minimum extent of dependency of UK patient organisations on pharmaceutical industry funding using drug company disclosure reports and patient organisation financial accounts from 2012 to 2016. We used linear regression to explain the overall share of industry funding (‘general dependency’) and top donor funding (‘company-specific dependency’) in organisations’ income. Predictors in

Just or Unjust : Assessment of rainfall-related flood damage in a Swedish context

Climate change has led to an increase in heavy summer rainfalls, and climate projections for Sweden indicate that there will be more sudden rainfall in the future. While the exact locations and time for this rainfall are unknown, it is known that there will be damages to buildings, cars, and people when the rainfall occurs. It is thus important to evaluate past events to understand the resulting fClimate change has led to an increase in heavy summer rainfalls, and climate projections for Sweden indicate that there will be more sudden rainfall in the future. While the exact locations and time for this rainfall are unknown, it is known that there will be damages to buildings, cars, and people when the rainfall occurs. It is thus important to evaluate past events to understand the resulting f

Water level management of wetlands in response to current and future RCP climate change scenarios : A mesocosm experiment within climate control chambers

Wetlands are integral components of our natural environment since they provide many critical ecosystem services to humanity, such as water purification, climate change mitigation, flood control, and biodiversity. Although wetlands can convey resilience to some degree of changes, they might be vulnerable to climate change. Altered hydrology and rising temperatures can turn the wetland services into

Test Optimization for Core-based System-on-Chip

The semiconductor technology has enabled the fabrication of integrated circuits (ICs), which may include billions of transistors and can contain all necessary electronic circuitry for a complete system, so-called System-on-Chip (SOC). In order to handle design complexity and to meet short time-to-market requirements, it is increasingly common to make use of a modular design approach where an SOC i

Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure

We develop an LM test for Granger causality in high-dimensional (HD) vector autoregressive (VAR) models based on penalized least squares estimations. To obtain a test retaining the appropriate size after the variable selection done by the lasso, we propose a post-double-selection procedure to partial out effects of nuisance variables and establish its uniform asymptotic validity. We conduct an ext

Transcranial direct current stimulation based on qEEG combining positive psychotherapy for major depression

Frontal cortex activity is reduced in the left hemisphere during depression. Transcranial direct current stimulation is a noninvasive neuromodulation technique that can increase frontal cortex activity. Therapy based on transcranial Direct Current Stimulation and positive psychology therapy was applied for improving patients' quality of life. The present study compared three conditions of subjects

The TECO Connectionist Theory of Recognition Failure

Data from experiments on the phenomenon of recognition failure of recallable words show moderate dependence between recognition and recall. TECO, a connectionist theory, is proposed to account for the phenomenon. Cued recall is assumed to be cued with the cue word and the event. Recognition is assumed to be cued with the event and the copy cue. Moderate dependence is predicted because recall and r

Remembering, Knowing and the Tulving-Wiseman Law

The Tulving-Wiseman law is an empirical law that describes the relation between successive tests of recognition and recall of the same set of individual subject-items. It relates the probability of recognising the recallable items to the probability of recognising all the items, regardless of whether they are recalled. The relation represents a moderate degree of dependency between the tests. Two

Successive Tests of Pair Recognition

A large number of experiments have found a moderate degree of dependence between subsequent tests of recognition and cued recall as described by the TW-function. This paper investigates the dependence in word pair recognition. Tests of word pair recognition are conducted with the subsequent test being free recall, cued recall, recognition, and cued recognition. The dependence is compared to subseq

Power function forgetting curves as an emergent property of biologically plausible neural network models

Empirical forgetting curve data have been shown to follow a power function. In contrast, many connectionist models predict either an exponential decay or flat forgetting curves. This paper simulates power function forgetting curves in a Hopfield network modified to incorporate the more biologically realistic assumptions of bounded weights and a distribution of learning rates. The modified model pr

The TECO theory and lawful dependency in successive episodic memory tests

A large number of experiments in successive tests of episodic memory have focused on an experimental paradigm called recognition failure of recallable words. In this paradigm, a cued recall test follows a recognition test. Large amounts of data have revealed a lawful moderate dependence between recognition and cued recall. TECO (Sikström, 1996b), a general connectionist theory of memory, has been

The variance theory of the mirror effect in recognition memory

The mirror effect refers to a rather general empirical finding showing that, for two classes of stimuli, the class with the higher hit rates also has a lower false alarm rate. In this article, a parsimonious theory is proposed to account for the mirror effect regarding, specifically, high- and low-frequency items and the associated receiver-operating curves. The theory is implemented in a recurren

Aging cognition : From neuromodulation to representation

Basic cognitive functions, such as the abilities to activate, represent, maintain, focus and process information, decline with age. A paradigm shift towards cross-level conceptions is needed in order to obtain an integrative understanding of cognitive aging phenomena that cuts across neural, information-processing, and behavioral levels. We review empirical data at these different levels, and comp

The power integration diffusion model for production breaks

The learning curve during repetitive production and the associated forgetting during production breaks are fundamental issues in the understanding of behavior. A model is suggested that combines 3 basic findings, namely, that single memory traces decay according to a power function of the retention interval, that aggregated memory traces can be combined by integration, and that the time to produce

Forgetting curves : Implications for connectionist models

Forgetting in long-term memory, as measured in a recall or a recognition test, is faster for items encoded more recently than for items encoded earlier. Data on forgetting curves fit a power function well. In contrast, many connectionist models predict either exponential decay or completely flat forgetting curves. This paper suggests a connectionist model to account for power-function forgetting c

Integrative neurocomputational perspectives on cognitive aging, neuromodulation, and representation

Besides neuroanatomical changes, neuromodulatory mechanisms are also compromised during aging. Neural network models are suitable tools for exploring the relatively broad and homogenous neuromodulatory influences on cortical function. Computational approaches for understanding neuromodulation of the dynamic properties of cortical function and recent neurocomputational theories relating different a