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https://www.readbyqxmd.com/read/28438009/modulation-format-free-and-automatic-bias-control-for-optical-iq-modulators-based-on-dither-correlation-detection
#1
Xiaolei Li, Lei Deng, Xiaoman Chen, Mengfan Cheng, Songnian Fu, Ming Tang, Deming Liu
A novel automatic bias control (ABC) method for optical in-phase and quadrature (IQ) modulator is proposed and experimentally demonstrated. In the proposed method, two different low frequency sine wave dither signals are generated and added on to the I/Q bias signal respectively. Instead of power monitoring of the harmonics of the dither signal, dither-correlation detection is proposed and used to adjust the bias voltages of the optical IQ modulator. By this way, not only frequency spectral analysis isn't required but also the directional bias adjustment could be realized, resulting in the decrease of algorithm complexity and the growth of convergence rate of ABC algorithm...
April 17, 2017: Optics Express
https://www.readbyqxmd.com/read/28437571/label-free-high-temporal-resolution-assessment-of-cell-proliferation-using-digital-holographic-microscopy
#2
Birgit Janicke, Andreas Kårsnäs, Peter Egelberg, Kersti Alm
Cell proliferation assays are widely applied in biological sciences to understand the effect of drugs over time. However, current methods often assess cell population growth indirectly, that is, the cells are not actually counted. Instead other parameters, for example, the amount of protein, are determined. These methods often also demand phototoxic labels, have low temporal resolution, or employ end-point assays, and frequently are labor intensive. We have developed a robust and label-free kinetic cell proliferation assay with high temporal resolution for adherent cells using digital holographic microscopy (DHM), one of many quantitative phase microscopy techniques...
April 24, 2017: Cytometry. Part A: the Journal of the International Society for Analytical Cytology
https://www.readbyqxmd.com/read/28437528/automated-staging-of-age-related-macular-degeneration-using-optical-coherence-tomography
#3
Freerk G Venhuizen, Bram van Ginneken, Freekje van Asten, Mark J J P van Grinsven, Sascha Fauser, Carel B Hoyng, Thomas Theelen, Clara I Sánchez
Purpose: To evaluate a machine learning algorithm that automatically grades age-related macular degeneration (AMD) severity stages from optical coherence tomography (OCT) scans. Methods: A total of 3265 OCT scans from 1016 patients with either no signs of AMD or with signs of early, intermediate, or advanced AMD were randomly selected from a large European multicenter database. A machine learning system was developed to automatically grade unseen OCT scans into different AMD severity stages without requiring retinal layer segmentation...
April 1, 2017: Investigative Ophthalmology & Visual Science
https://www.readbyqxmd.com/read/28437469/virtual-race-transformation-reverses-racial-in-group-bias
#4
Béatrice S Hasler, Bernhard Spanlang, Mel Slater
People generally show greater preference for members of their own racial group compared to racial out-group members. This type of 'in-group bias' is evident in mimicry behaviors. We tend to automatically mimic the behaviors of in-group members, and this behavior is associated with interpersonal sensitivity and empathy. However, mimicry is reduced when interacting with out-group members. Although race is considered an unchangeable trait, it is possible using embodiment in immersive virtual reality to engender the illusion in people of having a body of a different race...
2017: PloS One
https://www.readbyqxmd.com/read/28437440/synthesizer-expediting-synthesis-studies-from-context-free-data-with-information-retrieval-techniques
#5
Lisa M Gandy, Jordan Gumm, Benjamin Fertig, Anne Thessen, Michael J Kennish, Sameer Chavan, Luigi Marchionni, Xiaoxin Xia, Shambhavi Shankrit, Elana J Fertig
Scientists have unprecedented access to a wide variety of high-quality datasets. These datasets, which are often independently curated, commonly use unstructured spreadsheets to store their data. Standardized annotations are essential to perform synthesis studies across investigators, but are often not used in practice. Therefore, accurately combining records in spreadsheets from differing studies requires tedious and error-prone human curation. These efforts result in a significant time and cost barrier to synthesis research...
2017: PloS One
https://www.readbyqxmd.com/read/28437115/development-and-implementation-of-advanced-fitting-methods-for-the-calculation-of-accurate-molecular-structures
#6
Marco Mendolicchio, Emanuele Penocchio, Daniele Licari, Nicola Tasinato, Vincenzo Barone
The determination of accurate equilibrium molecular structures plays a fundamental role for understanding many physical-chemical properties of molecules, ranging from the precise evaluation of the electronic structure to the analysis of dynamical and environmental effects in tuning their overall behavior. For this purpose the so-called semi-experimental approach, based on a non-linear least-squares fit of the moments of inertia associated to a set of available isotopologues, allows one to obtain very accurate results, without the unfavorable computational cost characterizing high-level quantum chemical methods...
April 24, 2017: Journal of Chemical Theory and Computation
https://www.readbyqxmd.com/read/28436873/predicting-the-quality-of-fused-long-wave-infrared-and-visible-light-images
#7
David Moreno-Villamarin, Hernan Benitez-Restrepo, Alan Bovik
The capability to automatically evaluate the quality of long wave infrared (LWIR) and visible light images has the potential to play an important role in determining and controlling the quality of a resulting fused LWIR-visible light image. Extensive work has been conducted on studying the statistics of natural LWIR and visible images. Nonetheless, there has been little work done on analyzing the statistics of fused LWIR and visible images and associated distortions. In this paper, we analyze five multi-resolution based image fusion methods in regards to several common distortions, including blur, white noise, JPEG compression, and non-uniformity (NU)...
April 19, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28436853/automatic-skin-lesion-segmentation-using-deep-fully-convolutional-networks-with-jaccard-distance
#8
Yading Yuan, Ming Chao, Yeh-Chi Lo
Automatic skin lesion segmentation in dermoscopic images is a challenging task due to the low contrast between lesion and the surrounding skin, the irregular and fuzzy lesion borders, the existence of various artifacts, and various imaging acquisition conditions. In this article, we present a fully automatic method for skin lesion segmentation by leveraging a 19-layer deep convolutional neural networks (CNNs) that is trained end-to- end and does not rely on prior knowledge of the data. We propose a set of strategies to ensure effective and efficient learning with limited training data...
April 18, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28436849/reverse-classification-accuracy-predicting-segmentation-performance-in-the-absence-of-ground-truth
#9
Vanya V Valindria, Ioannis Lavdas, Wenjia Bai, Konstantinos Kamnitsas, Eric O Aboagye, Andrea G Rockall, Daniel Rueckert, Ben Glocker
When integrating computational tools such as automatic segmentation into clinical practice, it is of utmost importance to be able to assess the level of accuracy on new data, and in particular, to detect when an automatic method fails. However, this is difficult to achieve due to absence of ground truth. Segmentation accuracy on clinical data might be different from what is found through cross-validation because validation data is often used during incremental method development, which can lead to overfitting and unrealistic performance expectations...
April 17, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28436845/drawing-and-recognizing-chinese-characters-with-recurrent-neural-network
#10
Xu-Yao Zhang, Fei Yin, Yan-Ming Zhang, Cheng-Lin Liu, Yoshua Bengio
Recent deep learning based approaches have achieved great success on handwriting recognition. Chinese characters are among the most widely adopted writing systems in the world. Previous research has mainly focused on recognizing handwritten Chinese characters. However, recognition is only one aspect for understanding a language, another challenging and interesting task is to teach a machine to automatically write (pictographic) Chinese characters. In this paper, we propose a framework by using the recurrent neural network (RNN) as both a discriminative model for recognizing Chinese characters and a generative model for drawing (generating) Chinese characters...
April 18, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28436839/automatic-subretinal-fluid-segmentation-of-retinal-sd-oct-images-with-neurosensory-retinal-detachment-guided-by-enface-fundus-imaging
#11
Menglin Wu, Qiang Chen, Xiaojun He, Ping Li, Wen Fan, Songtao Yuan, Hyunjin Park
OBJECTIVE: Accurate segmentation of neurosensory retinal detachment (NRD)-associated subretinal fluid in spectral domain optical coherence tomography (SD-OCT) is vital for the assessment of central serous chorioretinopathy (CSC). A novel two-stage segmentation algorithm was proposed, guided by Enface fundus imaging. METHODS: In the first stage, Enface fundus image was segmented using thickness map prior to detecting the fluid-associated abnormalities with diffuse boundaries...
April 18, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28436492/a-multi-crystal-method-for-extracting-obscured-crystallographic-states-from-conventionally-uninterpretable-electron-density
#12
Nicholas M Pearce, Tobias Krojer, Anthony R Bradley, Patrick Collins, Radosław P Nowak, Romain Talon, Brian D Marsden, Sebastian Kelm, Jiye Shi, Charlotte M Deane, Frank von Delft
In macromolecular crystallography, the rigorous detection of changed states (for example, ligand binding) is difficult unless signal is strong. Ambiguous ('weak' or 'noisy') density is experimentally common, since molecular states are generally only fractionally present in the crystal. Existing methodologies focus on generating maximally accurate maps whereby minor states become discernible; in practice, such map interpretation is disappointingly subjective, time-consuming and methodologically unsound. Here we report the PanDDA method, which automatically reveals clear electron density for the changed state-even from inaccurate maps-by subtracting a proportion of the confounding 'ground state'; changed states are objectively identified from statistical analysis of density distributions...
April 24, 2017: Nature Communications
https://www.readbyqxmd.com/read/28436482/pathospotter-k-a-computational-tool-for-the-automatic-identification-of-glomerular-lesions-in-histological-images-of-kidneys
#13
George O Barros, Brenda Navarro, Angelo Duarte, Washington L C Dos-Santos
PathoSpotter is a computational system designed to assist pathologists in teaching about and researching kidney diseases. PathoSpotter-K is the version that was developed to detect nephrological lesions in digital images of kidneys. Here, we present the results obtained using the first version of PathoSpotter-K, which uses classical image processing and pattern recognition methods to detect proliferative glomerular lesions with an accuracy of 88.3 ± 3.6%. Such performance is only achieved by similar systems if they use images of cell in contexts that are much less complex than the glomerular structure...
April 24, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28436410/a-new-approach-to-develop-computer-aided-diagnosis-scheme-of-breast-mass-classification-using-deep-learning-technology
#14
Yuchen Qiu, Shiju Yan, Rohith Reddy Gundreddy, Yunzhi Wang, Samuel Cheng, Hong Liu, Bin Zheng
PURPOSE: To develop and test a deep learning based computer-aided diagnosis (CAD) scheme of mammograms for classifying between malignant and benign masses. METHODS: An image dataset involving 560 regions of interest (ROIs) extracted from digital mammograms was used. After down-sampling each ROI from 512×512 to 64×64 pixel size, we applied an 8 layer deep learning network that involves 3 pairs of convolution-max-pooling layers for automatic feature extraction and a multiple layer perceptron (MLP) classifier for feature categorization to process ROIs...
April 18, 2017: Journal of X-ray Science and Technology
https://www.readbyqxmd.com/read/28436271/divided-attention-enhances-the-recognition-of-emotional-stimuli-evidence-from-the-attentional-boost-effect
#15
Clelia Rossi-Arnaud, Pietro Spataro, Marco Costanzi, Daniele Saraulli, Vincenzo Cestari
The present study examined predictions of the early-phase-elevated-attention hypothesis of the attentional boost effect (ABE), which suggests that transient increases in attention at encoding, as instantiated in the ABE paradigm, should enhance the recognition of neutral and positive items (whose encoding is mostly based on controlled processes), while having small or null effects on the recognition of negative items (whose encoding is primarily based on automatic processes). Participants were presented a sequence of negative, neutral and positive stimuli (pictures in Experiment 1, words in Experiment 2) associated to target (red) squares, distractor (green) squares or no squares (baseline condition)...
April 23, 2017: Memory
https://www.readbyqxmd.com/read/28436249/the-weapon-focus-effect-is-weaker-with-black-versus-white-male-perpetrators
#16
Kerri L Pickel, Danielle E Sneyd
We compared the influence of a weapon's presence on eyewitnesses' memory for a White versus a Black male perpetrator. Prior data indicate that unusual objects in visual scenes attract attention and that a weapon's effect depends on how unusual it seems within the context in which it appears. Therefore, given the stereotype linking Black men and weapons, we predicted a weaker weapon focus effect with the Black perpetrator. The results of Experiment 1 supported this hypothesis using White and Black witnesses...
April 23, 2017: Memory
https://www.readbyqxmd.com/read/28436072/real-time-individualization-of-the-unified-model-of-performance
#17
Jianbo Liu, Sridhar Ramakrishnan, Srinivas Laxminarayan, Thomas J Balkin, Jaques Reifman
Existing mathematical models for predicting neurobehavioural performance are not suited for mobile computing platforms because they cannot adapt model parameters automatically in real time to reflect individual differences in the effects of sleep loss. We used an extended Kalman filter to develop a computationally efficient algorithm that continually adapts the parameters of the recently developed Unified Model of Performance (UMP) to an individual. The algorithm accomplishes this in real time as new performance data for the individual become available...
April 24, 2017: Journal of Sleep Research
https://www.readbyqxmd.com/read/28436004/engineering-of-an-h2-o2-auto-scavenging-in-vivo-cascade-for-pinoresinol-production
#18
Yongkun Lv, Xiaozhong Cheng, Guocheng Du, Jingwen Zhou, Jian Chen
Pinoresinol is a natural lignan with a high market value that has potential pharmacological and food supplement applications. Pinoresinol is currently isolated from plants, which suffers from low efficiency and yield. To produce pinoresinol from inexpensive and industrially available eugenol, an in vivo enzymatic cascade composed of vanillyl alcohol oxidase and peroxidase was designed, which scavenges H2 O2 automatically and eliminates protein purification and cofactor addition. Two peroxidases were screened and identified from Escherichia coli BL21 (DE3), and tested in the enzymatic cascade...
April 24, 2017: Biotechnology and Bioengineering
https://www.readbyqxmd.com/read/28435015/using-classification-models-for-the-generation-of-disease-specific-medications-from-biomedical-literature-and-clinical-data-repository
#19
Liqin Wang, Peter J Haug, Guilherme Del Fiol
OBJECTIVE: Mining disease-specific associations from existing knowledge resources can be useful for building disease-specific ontologies and supporting knowledge-based applications. Many association mining techniques have been exploited. However, the challenge remains when those extracted associations contained much noise. It is unreliable to determine the relevance of the association by simply setting up arbitrary cut-off points on multiple scores of relevance; and it would be expensive to ask human experts to manually review a large number of associations...
April 20, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28434747/bivariate-threshold-models-for-genetic-evaluation-of-susceptibility-to-and-ability-to-recover-from-mastitis-in-danish-holstein-cows
#20
B G Welderufael, L L G Janss, D J de Koning, L P Sørensen, P Løvendahl, W F Fikse
Mastitis in dairy cows is an unavoidable problem and genetic variation in recovery from mastitis, in addition to susceptibility, is therefore of interest. Genetic parameters for susceptibility to and recovery from mastitis were estimated for Danish Holstein-Friesian cows using data from automatic milking systems equipped with online somatic cell count measuring units. The somatic cell count measurements were converted to elevated mastitis risk, a continuous variable [on a (0-1) scale] indicating the risk of mastitis...
April 20, 2017: Journal of Dairy Science
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