Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations

Recent advances in scanning transmission electron and scanning probe microscopies have opened exciting opportunities in probing the materials structural parameters and various functional properties in real space with angstrom-level precision. This progress has been accompanied by an exponential increase in the size and quality of datasets produced by microscopic and spectroscopic experimental techniques. These developments necessitate adequate methods for extracting relevant physical and chemical information from the large datasets, for which a priori information on the structures of various atomic configurations and lattice defects is limited or absent. Here we demonstrate an application of deep neural networks to extract information from atomically resolved images including location of the atomic species and type of defects. We develop a 'weakly-supervised' approach that uses information on the coordinates of all atomic species in the image, extracted via a deep neural network, to identify a rich variety of defects that are not part of an initial training set. We further apply our approach to interpret complex atomic and defect transformation, including switching between different coordination of silicon dopants in graphene as a function of time, formation of peculiar silicon dimer with mixed 3-fold and 4-fold coordination, and the motion of molecular 'rotor'. This deep learning based approach resembles logic of a human operator, but can be scaled leading to significant shift in the way of extracting and analyzing information from raw experimental data

Probabilistic trend detection in different levels of consciousness

We aimed to explore how alertness modulates the management of probabilistic information in order to accurately detect changing patterns in a stream of conflicting evidence. We hypothesized that a decreased level of alertness might disrupt the strategy deployed to approach a probabilistic reversal learning task by impairment of working memory, of integration and value-updating of each piece of evidence, and decreased cognitive control. Our results showed that performance in probabilistic reversal learning is altered in decreased alertness, in relation to a higher frequency of spontaneous switching between patterns. Besides, response time and type suggest an impaired ability to generate a stable evidence-based strategy, although evidence-driven responses are present even in heavy drowsiness

An Examination of Hippocampal and Prefrontal Contributions to Spatial Learning and Memory using Immediate Early Gene Imaging

The hippocampus and medial prefrontal cortex are two brain regions which have repeatedly been linked to spatial learning and memory processing; however, the precise roles of individual sub-regions within these areas continue to be debated. The Morris water maze is a well-known behavioural task used to measure spatial memory. Despite its popularity, the type of spatial information animals encode and ultimately rely on for accurate navigation in this task remains unclear. Therefore, the primary objectives of this thesis were to conduct an in-depth investigation into the use of navigation strategies during memory encoding and retrieval in the water maze, and to characterise the specific contributions of the hippocampus and medial prefrontal cortex to these processes using Immediate Early Genes (IEG) imaging. In addition, we investigated the mechanisms underlying neuronal activation by inhibiting ionotropic glutamate receptors (NMDA and AMPA) during or after spatial learning. We found novel evidence that the salience (or noticeability) of environmental cues significantly impacted the type of learning strategy used (i.e. simple or complex), and that increased training led to more flexible responding (i.e. strategy switching). We also discovered that NMDA receptor-mediated activation in area CA1 (indexed by Zif268) was tightly linked to learning-related plasticity, and activation in CA3, prelimbic and anterior cingulate cortices was strongly associated with flexible spatial memory recall (i.e. pattern completion). Finally, we revealed that spatial memory deficits induced by NMDA receptor blockade could be partially prevented by extended environmental experience

ANALISIS PERILAKU KONSUMEN MUSLIM DAN PERILAKU EXPENDITURE SWITCHING KONSUMEN MUSLIM TERHADAP KONSUMSI KOSMETIK BERLABEL HALAL

Consumption activities can not be separated from human life. For Muslims, Halal is an absolute requirement for every product to be consumed, including cosmetic products. Labeled halal cosmetics has increased in the Indonesian market. However, still many muslim consumers who do not using labeled halal cosmetics surrounding researcher. Halal labeling considered a capable easier for consumers to obtain information about halal products to be consumed. This research aims to analyze Muslim consumer behavior in consuming halal cosmetic also to analyze expenditure switching behavior in cosmetic consumption. This research used purposive samping method, specified criteria are: female bachelor students of FEB Undip, Moslem, and using cosmetics. Number of samples is 94 respondents were determined using the method Slovin. This research use descriptive analysis, principal component analysis and logistic regression analysis. Descriptive statistical analysis is used to identify the respondent characteristics and some respondent’s direct answers. Principal Component Analysis (PCA) is used to reduce the questions of the original variables into uncorrelated variables construct and able to absorb most of the original variable information. Results of PCA can reduce 57 questions to 15 variables construct questions. Logistic regression was performed to analyze the effect of fifteen variables constructs and variables on the dependent variable income. The results of logistic regression showed that the behavior of Muslim consumers in the consumption of cosmetics labeled halal driven by: (1) Price non-nominal cosmetics without the halal label, (2) religiosity dimensions of knowledge, (3) type of the peer group, (4) learning, (5) Quality internal product, and (6) external quality of the product. While the switching pattern of consumer expenditure is largely driven by the type of the peer group

Screen captures to support switching attention

The study set out to validate the supportive role of screen captures for switching attention. Forty-two participants learned how to work with Microsoft Excel with a paper manual. There were three types of manuals: a textual manual, a visual manual with full-screen captures, and a visual manual with a mixture of partial- and full-screen captures. The findings show that participants in all conditions looked up from the manual to the screen on about 97% of the cases in which such a switch was called for rank order analyses showed that users of the visual manuals switched attention significantly more often than did users of the textual manual. No differences were found between conditions on learning effects and training time

Customer anger and incentives for quality provision

Emotions are a significant determinant of consumer behaviour. A customer may get angry if he feels that he is being treated unfairly by his supplier and that anger may make him more likely to switch to an alternative provider. We model the strategic interaction between firms that choose quality levels and anger-prone customers who pick their supplier based on their expectations of suppliers' quality. Strategic interaction can allow for multiple equilibria including some in which no firm invests in high quality. Allowing customers to voice their anger on peer-review fora can eliminate low-quality equilibria, and may even support a unique equilibrium in which all firms choose high quality

Peer Effects in Risk Taking

This paper examines the effect of peers on individual risk taking. In the absence of informational motives, we investigate why social utility concerns may drive peer effects. We test for two main channels: utility from payoff differences and from conforming to the peer. We show experimentally that social utility generates substantial peer effects in risk taking. These are mainly explained by utility from payoff differences, in line with outcomebased social preferences. Contrary to standard assumptions, we show that estimated social preference parameters change significantly when peers make active choices, compared to when lotteries are randomly assigned to them

Impact of information cost and switching of trading strategies in an artificial stock market

This paper studies the switching of trading strategies and its effect on the market volatility in a continuous double auction market. We describe the behavior when some uninformed agents, who we call switchers, decide whether or not to pay for information before they trade. By paying for the information they behave as informed traders. First we verify that our model is able to reproduce some of the stylized facts in real financial markets. Next we consider the relationship between switching and the market volatility under different structures of investors. We find that there exists a positive relationship between the market volatility and the percentage of switchers. We therefore conclude that the switchers are a destabilizing factor in the market. However, for a given fixed percentage of switchers, the proportion of switchers that decide to buy information at a given moment of time is negatively related to the current market volatility. In other words, if more agents pay for information to know the fundamental value at some time, the market volatility will be lower. This is because the market price is closer to the fundamental value due to information diffusion between switchers.Comment: 15 pages, 9 figures, Physica A, 201