Frequency multiplexed superconducting quantum interference device readout of large bolometer arrays for cosmic microwave background measurements

A technological milestone for experiments employing transition edge sensor bolometers operating at sub-Kelvin temperature is the deployment of detector arrays with 100s-1000s of bolometers. One key technology for such arrays is readout multiplexing: the ability to read out many sensors simultaneously on the same set of wires. This paper describes a frequency-domain multiplexed readout system which has been developed for and deployed on the APEX-SZ and South Pole Telescope millimeter wavelength receivers. In this system, the detector array is divided into modules of seven detectors, and each bolometer within the module is biased with a unique ～MHz sinusoidal carrier such that the individual bolometer signals are well separated in frequency space. The currents from all bolometers in a module are summed together and pre-amplified with superconducting quantum interference devices operating at 4 K. Room temperature electronics demodulate the carriers to recover the bolometer signals, which are digitized separately and stored to disk. This readout system contributes little noise relative to the detectors themselves, is remarkably insensitive to unwanted microphonic excitations, and provides a technology pathway to multiplexing larger numbers of sensors.     

Using retina modelling to characterize blinking: comparison between EOG and video analysis

A large number of car crashes are caused by drowsiness every year. The analysis of eye blinks provides reliable information about drowsiness. This paper proposes to study the relation between electrooculogram (EOG) and video analysis for blink detection and characterization. An original method to detect and characterize blinks from a video analysis is presented here. The method uses different filters based on the human retina modelling. A illumination robust filter is first used to normalize illumination variations of the video input. Then, Outer and an Inner Plexiform Layer filters are used to extract energy signals from eye area. The eye detection is processed mixing gradient and projection methods which makes it able to detect even closed eyes. The illumination robust filter makes it possible to detect the eyes even in night conditions, without using external lighting. The video analysis extracts two signals from the eye area measuring the quantity of static edges and moving edges. Blinks are then detected and characterized from these two signals. A comparison between the features extracted from the EOG and the same features extracted from the video analysis is then performed on a database of 14 different people. This study shows that some blink features extracted from the video are highly correlated with their EOG equivalent: the duration, the duration at 50%, the frequency, the percentage of eye closure at 80% and the amplitude velocity ratio. The frame rate influence on the accuracy of the different features extracted is also studied and enlightens on the need of a high frame rate camera to detect and characterize accurately blinks from a video analysis.     

A Simon Effect in Pigeons.

Pigeons pecked left versus right keys contingent upon the color presented at 1 of those locations. Spatial-response latencies were shorter when the color appeared at the same location as the required response than at the opposite location. This Simon effect occurred when the stimulus on the alternative key was constant, varied from trial to trial, or changed when the color cue appeared and when the reinforcement probability for correct responses was the same on corresponding as on noncorresponding trials. Humans performing the same task by touching the keys also showed the Simon effect. These findings demonstrate that for pigeons, too, a relevant symbolic cue activates a spatial code that produces faster responses at the location corresponding with the activated code. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An overview of recommender systems in the healthy food domain

Recently, food recommender systems have received increasing attention due to their relevance for healthy living. Most existing studies on the food domain focus on recommendations that suggest proper food items for individual users on the basis of considering their preferences or health problems. These systems also provide functionalities to keep track of nutritional consumption as well as to persuade users to change their eating behavior in positive ways. Also, group recommendation functionalities are very useful in the food domain, especially when a group of users wants to have a dinner together at home or have a birthday party in a restaurant. Such scenarios create many challenges for food recommender systems since the preferences of all group members have to be taken into account in an adequate fashion. In this paper, we present an overview of recommendation techniques for individuals and groups in the healthy food domain. In addition, we analyze the existing state-of-the-art in food recommender systems and discuss research challenges related to the development of future food recommendation technologies.     

Mechanical properties of continuous bamboo fiber-reinforced biobased polyamide 11 composites

This study is devoted to the analysis of the properties of continuous bamboo fiber (BF)-reinforced polyamide 11 (PA 11) composites. The SEM observations highlighted continuity between BFs and the polymeric matrix showing a high density of hydrogen bonds. The comparative calorimetric study of the matrix and its composites showed that the crystallinity of PA 11 was not modified by the presence of bamboo fibers. The physical aging observed in PA 11 is no more observed in composites due to physical interactions between PA 11 and BFs. The mechanical properties were investigated by tensile strength and dynamic mechanical analysis. The introduction of BFs enhanced Young's modulus of the matrix by a factor of 10. The presence of BFs also improved the storage shear modulus G′ over the whole temperature range. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47623.     

Brewing of glucuronic acid-enriched apple cider with enhanced antioxidant activities through the co-fermentation of yeast (Saccharomyces cerevisiae and Pichia kudriavzevii) and bacteria (Lactobacillus plantarum)

Co-fermentation using yeast (Saccharomyces cerevisiae and Pichia kudriavzevii) and the bacteria (Lactobacillus plantarum) as starters isolated from spontaneous sourdough was conducted for the brewing of glucuronic acid (GlcA)-enriched apple cider. The concentration of GlcA in the apple cider co-fermented for 14 d with commercial S. cerevisiae and L. plantarum was 37.7 ± 1.7 mg/mL while a concentration of 62.8 ± 3.1 mg/mL was recorded for fermentation with P. kudriavzevii and L. plantarum, which was higher than the corresponding single yeast fermentation. The co-fermented apple cider revealed higher 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity of 171.67 ± 0.79 µg trolox equivalents (TE)/mL using P. kudriavzevii and L. plantarum, compared to the control (143.89 ± 7.07 µg TE/mL) just using S. cerevisiae. Thus, the co-fermentation of S. cerevisiae and L. plantarum and P. kudriavzevii and L. plantarum provided a new strategy for the development of GlcA-enriched apple cider with enhanced antioxidant capacity.     

Unsupervised joint face alignment with gradient correlation coefficient

This work proposes an unsupervised joint alignment framework, referred to as “Gradient Correlation Congealing,” which aligns an image ensemble by maximizing a sum of gradient correlation coefficient function defined over all images. We, respectively, develop two different formulations to optimize the objective function regarding the role of “template.” While most existing face alignment methods suffer from outliers, e.g., occlusions, the proposed algorithms are able to align faces undergoing partial occlusions. Moreover, our algorithms can cope with nonuniform illumination changes (even extremely difficult ones), and also, they do not require any predefined templates. We test the novel approaches against four typical joint alignment methods including Least-Squares Congealing, Learned-Miller Congealing, Lucas–Kanade entropy Congealing, and RASL using three challenging face databases: AR, Yale B, and LFW. Experimental results prove the efficiency of our approaches under different conditions, especially when faces are partially occluded, and the proposed algorithms perform much better than all considered methods.