A Study of Sediment Transport in Norwegian Glacial Rivers, 1969

From original report: The Norwegian Water Resources and Electricity Board, Institute of Water Resources, Department of Hydrology, Oslo. September 1970. Report No. 6/70.Permission to translate this Norwegian report was kindly given by G. Østrem, and the translation by Helga Carstens, while she was in Alaska, is greatly appreciated. Unfortunately, Mrs. Carstens returned to her homeland, Norway, before final editing of the manuscript could be completed. Consequently, any errors in translation are due to the editor, and for these errors, the editor apologizes to the authors. Not included in this translation is an English summary contained in the original report. To keep printing costs down, the original figures and tables, which fortunately had English titles, are used in this translation. This report is the first of a series of reports being prepared for the Norwegian Water Resources and Electricity Board. The second report for 1970 has been published with an English summary and contains an extension of the data contained in the 1969 report. Because this work deals with problems very similar to those in Alaska, it was decided to translate the first report and circulate a limited number of copies to workers in the U. S. and Canada. Research very similar to the Norwegian work was initiated in Alaska under the editor's direction in cooperation with the U. S. Geological Survey. -- G. L. Guymon.This work and the translation of this report were supported by funds provided by the United States Department of the Interior, Office of Water Resources Research (Proj. A-042-ALAS), as authorized under the amended Water Resources Act of 1964

Spatio-Temporal Sentiment Hotspot Detection Using Geotagged Photos

We perform spatio-temporal analysis of public sentiment using geotagged photo collections. We develop a deep learning-based classifier that predicts the emotion conveyed by an image. This allows us to associate sentiment with place. We perform spatial hotspot detection and show that different emotions have distinct spatial distributions that match expectations. We also perform temporal analysis using the capture time of the photos. Our spatio-temporal hotspot detection correctly identifies emerging concentrations of specific emotions and year-by-year analyses of select locations show there are strong temporal correlations between the predicted emotions and known events.Comment: To appear in ACM SIGSPATIAL 201

Emotion processing in infancy: specificity in risk for social anxiety and associations with two year outcomes

The current study examined the specificity of patterns of responding to high and low intensity negative emotional expressions of infants of mothers with social phobia, and their association with child outcomes at two years of age. Infants of mothers with social phobia, generalised anxiety disorder (GAD) or no history of anxiety were shown pairs of angry and fearful emotional expressions at 10 weeks of age. Symptoms of social withdrawal, anxiety and sleep problems were assessed at two years of age. Only infants of mothers with social phobia showed a tendency to look away from high intensity fear faces; however infants of mothers with both social phobia and GAD showed a bias towards high intensity angry faces. Among the offspring of mothers with social phobia, anxiety symptoms at two years of age were associated with a preference for high intensity fear faces in infancy. The reverse pattern was found amongst the offspring of non-anxious mothers. These findings suggest a possible specific response to emotional expressions among the children of mothers with social phobia

Distinguishing Posed and Spontaneous Smiles by Facial Dynamics

Smile is one of the key elements in identifying emotions and present state of mind of an individual. In this work, we propose a cluster of approaches to classify posed and spontaneous smiles using deep convolutional neural network (CNN) face features, local phase quantization (LPQ), dense optical flow and histogram of gradient (HOG). Eulerian Video Magnification (EVM) is used for micro-expression smile amplification along with three normalization procedures for distinguishing posed and spontaneous smiles. Although the deep CNN face model is trained with large number of face images, HOG features outperforms this model for overall face smile classification task. Using EVM to amplify micro-expressions did not have a significant impact on classification accuracy, while the normalizing facial features improved classification accuracy. Unlike many manual or semi-automatic methodologies, our approach aims to automatically classify all smiles into either `spontaneous' or `posed' categories, by using support vector machines (SVM). Experimental results on large UvA-NEMO smile database show promising results as compared to other relevant methods.Comment: 16 pages, 8 figures, ACCV 2016, Second Workshop on Spontaneous Facial Behavior Analysi

Deception and self-awareness

This paper presents a study conducted for the Shades of Grey EPSRC research project (EP/H02302X/1), which aims to develop a suite of interventions for identifying terrorist activities. The study investigated the body movements demonstrated by participants while waiting to be interviewed, in one of two conditions: preparing to lie or preparing to tell the truth. The effect of self-awareness was also investigated, with half of the participants sitting in front of a full length mirror during the waiting period. The other half faced a blank wall. A significant interaction was found for the duration of hand/arm movements between the deception and self-awareness conditions (F=4.335, df=1;76, p<0.05). Without a mirror, participants expecting to lie spent less time moving their hands than those expecting to tell the truth; the opposite was seen in the presence of a mirror. This finding indicates a new research area worth further investigation

Food Handling Practices for Fresh-Cut Vegetables at Wet Markets and Supermarkets in Davao City, Philippines

Fresh-cuts, either ready-to-cook (RTC) or ready-to-eat (RTE) fruits and vegetables, are becoming more popular due to consumers’ increasing demand for convenient and healthy foods. This paper aimed to document different fresh-cut vegetables available in wet markets and supermarkets in Davao City, Philippines, to differentiate fresh-cut processing practices between the two locations, and to identify some inadequacies in their practices. Overall, the fresh-cuts were available as either monotype (e.g. coconut pith, squash, and immature jackfruit) or mixed (e.g. pinakbet and chop suey). With regards to the pre- and post-cutting treatment, water was not always used since consumers were expected to wash them before cooking and/or eating. Water used for washing was also reused, which could be a source of contamination. During processing, inappropriate craft cutter blades were sometimes used in wet markets, which could lead to more produce injury that may result in more browning. Moreover, packaging was mostly used only upon purchase in the wet markets whereas supermarkets had more pre-packed options. Lastly, an evident observation was the temperature abuse (above 5°C) during storage in both locations. This poses a threat of pathogen contamination especially since visual indications of deterioration are not always obvious. Thus, interventions are recommended to educate fresh-cut processors in both wet markets and supermarkets about useful techniques in preserving the quality and safety of fresh-cut vegetables. Additional information on the degree of microbial contamination and shelf-life of these products may also aid in generating applicable food safety strategies. Keywords: fresh-cut practices · minimal processing · vegetable crop

Extended Calculations of Spectroscopic Data: Energy Levels, Lifetimes and Transition rates for O-like ions from Cr XVII to Zn XXIII

Employing two state-of-the-art methods, multiconfiguration Dirac--Hartree--Fock and second-order many-body perturbation theory, the excitation energies and lifetimes for the lowest 200 states of the $2s^2 2p^4$, $2s 2p^5$, $2p^6$, $2s^2 2p^3 3s$, $2s^2 2p^3 3p$, $2s^2 2p^3 3d$, $2s 2p^4 3s$, $2s 2p^4 3p$, and $2s 2p^4 3d$ configurations, and multipole (electric dipole (E1), magnetic dipole (M1), and electric quadrupole (E2)) transition rates, line strengths, and oscillator strengths among these states are calculated for each O-like ion from Cr XVII to Zn XXIII. Our two data sets are compared with the NIST and CHIANTI compiled values, and previous calculations. The data are accurate enough for identification and deblending of new emission lines from the sun and other astrophysical sources. The amount of data of high accuracy is significantly increased for the $n = 3$ states of several O-like ions of astrophysics interest, where experimental data are very scarce