Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU

The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia’s GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures

Anomalous crystalline ordering of particles in a viscoelastic fluid under high shear

Addition of particles to a viscoelastic suspension dramatically alters the properties of the mixture, particularly when it is sheared or otherwise processed. Shear-induced stretching of the polymers results in elastic stress that causes a substantial increase in measured viscosity with increasing shear, and an attractive interaction between particles, leading to their chaining. At even higher shear rates, the flow becomes unstable, even in the absence of particles. This instability makes it very difficult to determine the properties of a particle suspension. Here we use a fully immersed parallel plate geometry to measure the high-shear-rate behavior of a suspension of particles in a viscoelastic fluid. We find an unexpected separation of the particles within the suspension resulting in the formation of a layer of particles in the center of the cell. Remarkably, monodisperse particles form a crystalline layer which dramatically alters the shear instability. By combining measurements of the velocity field and torque fluctuations, we show that this solid layer disrupts the flow instability and introduces a new, single-frequency component to the torque fluctuations that reflects a dominant velocity pattern in the flow. These results highlight the interplay between particles and a suspending viscoelastic fluid at very high shear rates.Comment: SI Videos and future data sharing are available at https://doi.org/10.7910/DVN/K0XZ6

Algal blooms: how are they harming models used for climate management?

18th International Conference on Harmful Algae (ICHA 2018), 21-26 October 2018, Nantes, France.-- 4 pages, 2 figuresMicroalgae blooms are generally associated with bacterial secondary producers. They produce organic matter (OM), some of which associates with the sea surface microlayer (SML). OM in the SML below the actual surface reduces fluxes of energy, including heat and momentum, and substances, including greenhouse gases, aerosols, algae, bacteria and viruses. In addition to the SML-associated OM, another OM fraction, foam (including whitecaps), often lies above the primary SML when windspeeds exceed about 5 m s-1, trapping gas bubbles. Such foam also dramatically increases albedo, reflecting solar radiation back into space, thus reducing solar heating and penetration of photosynthetically active radiation. Mean coverage of the ocean surface by foam has been measured to range between 1-6%, particularly in zones of Trade Winds. Different types of OM, and particularly their mechanical properties, depend on ambient algal abundance, as well as on taxonomic composition, as do the dynamics of foam formation and decay. Air-sea fluxes may thus be influenced by genomic control through the blooming microalgae and Darwinian-type evolution. Bacteria may also play a role. In addition, foam patches on the ocean’s surface serve as a unique microbial habitat. Such blooms, particularly when their taxonomic composition changes unpredictably, are likely to be harming the usefulness of climate models. Some of this harm might be mitigated by studying the relevant effects of these blooms on fluxes, and incorporating these effects into climate modelsJS is supported by National Nature Science Foundation of China grant (41876134) and the Changjiang Scholar Program of Chinese Ministry of Educatio

Intrusion location technology of Sagnac distributed fiber optical sensing system based on deep learning

For distributed fiber optical sensing based on Sagnac effect, the intrusion is usually located by notch frequency. However, the notch spectrum is the comprehensive result of the intrusion, so when multiple disturbances simultaneously intrude from different positions of the sensing fiber, it is impossible to establish a mathematical expression between the intrusion position and the notch frequency, this leads to the problem of multi-point intrusion localization. Therefore, in this paper, deep learning technology is used to locate multiple disturbing points in Sagnac distributed optical fiber sensing system, and the related specific technologies of deep learning applying to sagnac distributed optical fiber sensing are studied. First, according to the characteristics of the system, a network structure based on the regression probability distribution is proposed, second, a loss function is constructed. The results show that the trained model can realize the positioning of multiple and single intrusion points

Individual participant data meta analysis to compare EPDS accuracy to detect major depression with and without the self-harm item

Item 10 of the Edinburgh Postnatal Depression Scale (EPDS) is intended to assess thoughts of intentional self-harm but may also elicit concerns about accidental self-harm. It does not specifically address suicide ideation but, nonetheless, is sometimes used as an indicator of suicidality. The 9-item version of the EPDS (EPDS-9), which omits item 10, is sometimes used in research due to concern about positive endorsements of item 10 and necessary follow-up. We assessed the equivalence of total score correlations and screening accuracy to detect major depression using the EPDS-9 versus full EPDS among pregnant and postpartum women. We searched Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science from database inception to October 3, 2018 for studies that administered the EPDS and conducted diagnostic classification for major depression based on a validated semi-structured or fully structured interview among women aged 18 or older during pregnancy or within 12 months of giving birth. We conducted an individual participant data meta-analysis. We calculated Pearson correlations with 95% prediction interval (PI) between EPDS-9 and full EPDS total scores using a random effects model. Bivariate random-effects models were fitted to assess screening accuracy. Equivalence tests were done by comparing the confidence intervals (CIs) around the pooled sensitivity and specificity differences to the equivalence margin of δ = 0.05. Individual participant data were obtained from 41 eligible studies (10,906 participants, 1407 major depression cases). The correlation between EPDS-9 and full EPDS scores was 0.998 (95% PI 0.991, 0.999). For sensitivity, the EPDS-9 and full EPDS were equivalent for cut-offs 7-12 (difference range - 0.02, 0.01) and the equivalence was indeterminate for cut-offs 13-15 (all differences - 0.04). For specificity, the EPDS-9 and full EPDS were equivalent for all cut-offs (difference range 0.00, 0.01). The EPDS-9 performs similarly to the full EPDS and can be used when there are concerns about the implications of administering EPDS item 10.This study was funded by the Canadian Institutes of Health Research (CIHR, KRS-140994). Dr. Qiu was supported by a scholarship from the China Scholarship Council. Drs. Wu and Levis were supported by Fonds de recherche du Québec—Santé (FRQ-S) Postdoctoral Training Fellowships. Dr. Benedetti was supported by a Fonds de recherche du Québec – Santé (FRQS) researcher salary award. Dr. Thombs was supported by a Tier 1 Canada Research Chair. Ms. Rice was supported by a Vanier Canada Graduate Scholarship. The primary study by Alvarado et al. was supported by the Ministry of Health of Chile. The primary study by Barnes et al. was supported by a grant from the Health Foundation (1665/608). The primary study by Beck et al. was supported by the Patrick and Catherine Weldon Donaghue Medical Research Foundation and the University of Connecticut Research Foundation. The primary study by Helle et al. was supported by the Werner Otto Foundation, the Kroschke Foundation, and the Feindt Foundation. The primary study by Figueira et al. was supported by the Brazilian Ministry of Health and by the National Counsel of Technological and Scientific Development (CNPq) (Grant no.403433/2004-5). The primary study by Couto et al. was supported by the National Counsel of Technological and Scientific Development (CNPq) (Grant no. 444254/2014-5) and the Minas Gerais State Research Foundation (FAPEMIG) (Grant no. APQ-01954-14). The primary study by Chorwe-Sungani et al. was supported by the University of Malawi through grant QZA-0484 NORHED 2013. The primary study by de Figueiredo et al. was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo. The primary study by Tissot et al. was supported by the Swiss National Science Foundation (grant 32003B 125493). The primary study by Fernandes et al. was supported by grants from the Child: Care Health and Development Trust and the Department of Psychiatry, University of Oxford, Oxford, UK, and by the Ashok Ranganathan Bursary from Exeter College, University of Oxford. Dr. Fernandes is supported by a University of Southampton National Institute for Health Research (NIHR) academic clinical fellowship in Paediatrics. The primary study by van Heyningen et al. was supported by the Medical Research Council of South Africa (fund no. 415865), Cordaid Netherlands (Project 103/10002 G Sub 7) and the Truworths Community Foundation Trust, South Africa. Dr. van Heyningen was supported by the National Research Foundation of South Africa and the Harry Crossley Foundation. VHYTHE001/1232209. The primary study by Tendais et al. was supported under the project POCI/SAU-ESP/56397/2004 by the Operational Program Science and Innovation 2010 (POCI 2010) of the Community Support Board III and by the European Community Fund FEDER. The primary study by Fisher et al. was supported by a grant under the Invest to Grow Scheme from the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs. The primary study by Green et al. was supported by a grant from the Duke Global Health Institute (453-0751). The primary study by Howard et al. was supported by the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Numbers RP-PG-1210-12002 and RP-DG-1108-10012) and by the South London Clinical Research Network. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. The primary study by Kettunen et al. was supported with an Annual EVO Financing (Special government subsidies from the Ministry of Health and Welfare, Finland) by North Karelia Central Hospital and Päijät-Häme Central Hospital. The primary study by Phillips et al. was supported by a scholarship from the National Health and Medical and Research Council (NHMRC). The primary study by Roomruangwong et al. was supported by the Ratchadaphiseksomphot Endowment Fund 2013 of Chulalongkorn University (CU-56-457-HR). The primary study by Martínez et al. was supported by Iniciativa Científica Milenio, Chile, process # IS130005 and by Fondo Nacional de Desarrollo Científico y Tecnológico, Chile, process # 1130230. The primary study by Nakić Radoš et al. was supported by the Croatian Ministry of Science, Education, and Sports (134-0000000-2421). The primary study by Usuda et al. was supported by Grant-in-Aid for Young Scientists (A) from the Japan Society for the Promotion of Science (primary investigator: Daisuke Nishi, MD, PhD), and by an Intramural Research Grant for Neurological and Psychiatric Disorders from the National Center of Neurology and Psychiatry, Japan. The primary study by Pawlby et al. was supported by a Medical Research Council UK Project Grant (number G89292999N). The primary study by Rochat et al. was supported by grants from the University of Oxford (HQ5035), the Tuixen Foundation (9940), the Wellcome Trust (082384/Z/07/Z and 071571), and the American Psychological Association. Dr. Rochat receives salary support from a Wellcome Trust Intermediate Fellowship (211374/Z/18/Z). The primary study by Rowe et al. was supported by the diamond Consortium, beyondblue Victorian Centre of Excellence in Depression and Related Disorders. The primary study by Comasco et al. was supported by funds from the Swedish Research Council (VR: 521-2013-2339, VR:523-2014-2342), the Swedish Council for Working Life and Social Research (FAS: 2011-0627), the Marta Lundqvist Foundation (2013, 2014), and the Swedish Society of Medicine (SLS-331991). The primary study by Smith-Nielsen et al. was supported by a grant from the charitable foundation Tryg Foundation (Grant ID no 107616). The primary study by Prenoveau et al. was supported by The Wellcome Trust (grant number 071571). The primary study by Stewart et al. was supported by Professor Francis Creed’s Journal of Psychosomatic Research Editorship fund (BA00457) administered through University of Manchester. The primary study by Su et al. was supported by grants from the Department of Health (DOH94F044 and DOH95F022) and the China Medical University and Hospital (CMU94-105, DMR-92-92 and DMR94-46). The primary study by Tandon et al. was funded by the Thomas Wilson Sanitarium. The primary study by Tran et al. was supported by the Myer Foundation who funded the study under its Beyond Australia scheme. Dr. Tran was supported by an early career fellowship from the Australian National Health and Medical Research Council. The primary study by Vega-Dienstmaier et al. was supported by Tejada Family Foundation, Inc, and Peruvian-American Endowment, Inc. The primary study by Yonkers et al. was supported by a National Institute of Child Health and Human Development grant (5 R01HD045735). No other authors reported funding for primary studies or for their work on this study

Combination of ozone-based advanced oxidation process and nanobubbles generation toward textile wastewater recovery

The intricate nature of various textile manufacturing processes introduces colored dyes, surfactants, and toxic chemicals that have been harmful to ecosystems in recent years. Here, a combination ozone-based advanced oxidation process (AOP) is coupled with a nanobubbles generator for the generation of ozone nanobubbles (NB) utilized the same to treat the primary effluent acquired from textile wastewaters. Here we find several key parameters such as chemical oxygen demand ammonia content (NH3), and total suspended solids indicating a substantial recovery in which the respective percentages of 81.1%, 30.81%, and 41.98%, upon 300 min residence time are achieved. On the other hand, the pH is shifted from 7.93 to 7.46, indicating the generation of hydrogen peroxide (H2O2) due to the termination reaction and the self-reaction of reactive oxygen species (ROS). We propose that the reactive oxygen species can be identified from the negative zeta potential measurement (−22.43 ± 0.34 mV) collected in the final state of treatment. The combined method has successfully generated ozone nanobubbles with 99.94% of size distributed in 216.9 nm. This highlights that enhancement of ozone’s reactivity plays a crucial role in improving the water quality of textile wastewater towards being technologically efficient to date