bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of refrigerated storage of UVC pathogen inactivated platelet concentrates on in vitro platelet quality parameters
Authors: Johnson Lacey , Cameron Mathew , Waters Lauren , Padula Matthew P. , Marks Denese C.
Published: November 2018

Background and Objectives

Refrigeration (cold‐storage) of pathogen inactivated (PI) platelet components may increase the shelf‐life and safety profile of platelet components, compared to conventional room‐temperature (RT) storage. Whilst there is substantial knowledge regarding the impact of these individual treatments on platelets, the combined effect has not been assessed.

Materials and methods

Using a pool‐and‐split study design, paired buffy‐coat derived platelets in 70% platelet additive solution (SSP+; MacoPharma) were left untreated or PI‐treated using the THERAFLEX UV‐Platelets System (UVC; MacoPharma). Units from each pair were split and stored at room temperature (20–24°C) or cold‐stored (2–6°C) to yield RT, cold, RT‐UVC and cold‐UVC study groups (n = 8 in each group). In vitro quality and function was tested over 9 days.

Results

Cold‐storage of UVC‐treated platelets reduced glycolytic metabolism (glucose consumption and lactate production) compared to RT‐UVC units. Cold‐UVC platelets demonstrated complete abrogation of HSR by day 5, increased externalisation of phosphatidylserine (annexin‐V binding) and activation of the GPIIb/IIIa receptor (PAC‐1 binding) above the levels observed with the individual treatments. Aggregation responses (ADP and collagen) were enhanced in the cold‐UVC platelets compared to both RT groups, but this was primarily mediated by cold‐storage. Haemostatic function, as measured using TEG, was similar between the groups.

Conclusion

Cold‐storage of UVC‐treated platelets reduced PI‐induced acceleration of glycolytic metabolism. However, combining cold‐storage and UVC‐treatment resulted in additional phenotypic changes compared to each treatment individually. Further work is required to understand the impact of these changes in clinical efficacy.
Uncertainty assessment of streamflow projection under the impact of climate change in the Lower Mekong Basin: a case study of the Srepok River Basin, Vietnam
Authors: Hoan Nguyen Xuan , Khoi Dao Nguyen , Nhi Pham Thi Thao
Published: November 2018

Uncertainty assessment of future projection of streamflow is of the essence for an effective formulation of water resources management and planning adaptive to climate change. The aim of this study is to investigate the uncertainty in streamflow projection under the climate change impact in the Srepok River Basin. Uncertainty associated with emission scenarios (RCP2.6, RCP4.5 and RCP8.5), General Circulation Models (GCMs) (CanESM2, CNMR‐CM5 and HadGEM2‐AO), statistical downscaling methods (delta change method, quantile mapping and SDSM), and hydrological models (ANN, HEC‐HMS and SWAT) is examined. The results showed the largest uncertainty source of the streamflow projection is the GCM simulations, followed by the statistical downscaling methods, hydrological models and emission scenarios. In addition, the use of hydrological models has a considerable impact on uncertainty in the simulations of dry seasonal streamflow. Generally, the present study highlighted the importance of using multi‐GCMs in the studies on hydrological impact of climate change.
Serological surveillance and factors associated with influenza A virus in backyard pigs in Southern Brazil
Authors: Souza Carine K. , Oldiges Daiane P. , Poeta Ana Paula S. , Vaz Itabajara da S. , Schaefer Rejane , Gava Danielle , Ciacci‐Zanella Janice R. , Canal Cláudio W. , Corbellini Luís G.
Published: November 2018

Backyard pig populations are not monitored for influenza A virus (IAV) in Brazil and there are limited data about seroprevalence and risk factors in these populations. Our goal was to assess possible factors associated with IAV seroprevalence in backyard pig populations using an indirect ELISA protocol based on a recombinant nucleoprotein. Following the IAV screening using NP‐ELISA, subtype‐specific serology based on hemagglutination inhibition (HI) assay of the ELISA‐positive pigs was conducted. The survey comprised a total of 1,667 sera samples collected in 2012 and 2014 in 479 holdings and the estimated seroprevalence was 5.3% (3.84%–7.33%) and 2.3% (1.34%–3.71%) in the respective years. In both years, H1N1pdm09 was the most prevalent subtype. The multivariable analysis showed main factors such as “age,” “sex,” “number of suckling pigs” and “neighbours raising pigs” that presented the greatest effect on IAV seroprevalence in these pig populations. These factors may be associated with the low biosecurity measures and management of backyard holdings. In addition, the low IAV seroprevalences found in these backyard pig populations could be related to a low number of animals in each pig holding and low animal movement/replacement that do not favour IAV transmission dynamics. This low frequency of H1N1pdm09 seropositive pigs could also be due to sporadic human‐to‐pig transmission of what is now a human seasonal influenza A virus; however, these factors should be explored in future studies. Herein, these results highlight the importance of IAV continued surveillance in backyard pig holdings, since it is poorly known which IAVs are circulating in these populations and the risk they could pose to public health and virus transmission to commercial farms.
Simulation as a Multidisciplinary Team Approach in Healthcare Programs in an Urban University Setting
Authors: Blue Dawn I. , Fike Geraldine C. , Escalante Guillermo , Kim Yeon , Munoz Jose A.
Published: November 2018

Background: In the hospital setting, patients are usually cared for by a nurse and multidisciplinary teams which may include physical therapists, social workers, and public health workers. However, students in health care programs usually will not experience interdisciplinary scenarios developing needed skills. Combining classes and replacing certain curriculum activities with patient simulation projects that include several departments may improve their educational experience and success. Simulation is technology used to enhance instruction resources for all students. Simulation not only captures the attention of the video-game generation but actively engages students in the learning process. Simulation can be a valuable experience to keep students actively involved in learning by offering the opportunity to apply knowledge learned to the clinical setting, thus making it real. It is compelling to consider the impact of simulation in increasing the competency of students when they are in the work force while decreasing error rate and impacting the quality of care.Methods: A mixed method approach involved simulation experience followed by data collection via survey.Results: Students across all disciplines reported increased ability for collaboration and communication.Conclusions: Demonstrated the value of introducing the students to teamwork and collaboration experiences via simulation.
Academic Motivation and Academic Self-efficacy of Prospective Teachers
Authors: Titrek Osman , Çetin Ceren , Kaymak Esra , Kaşikçi Merve Melike
Published: November 2018

The purpose of this study is to examine the relationships between academic self-efficacy perception of prospective teachers and their academic motivation levels. The study was conducted on 322 prospective teachers (226 female and 96 male) who were in 3rd and 4th grades at Faculty of Education in Sakarya University during Spring term of 2017-2018 academic year. Data was collected through “Academic Motivation Scale” developed by Vallerand et al. (1992) and adapted into Turkish by Karagüven (2012) and “Self-perception of Candidate Teachers on Teaching Proficiency Scale” developed by Çakır, Erkuş, and Kılıç (2004). SPSS 23 package program was used to analyze the data; percentage, frequency, arithmetic mean, standard deviation, independent samples t-test, one-way analysis of variance (ANOVA), Tukey HSD and Pearson Correlation test were used in the data analysis. The results of analyses indicated that academic self-efficacy perception levels of the prospective teachers were at desired level. However, their academic motivation levels were at middle level. The result of the analysis revealed that the prospective teachers who were female and taught at 4th grade had higher academic self-efficacy score whereas significant difference was not found in academic motivation levels in terms of gender and grade. On the other hand, there was a significant difference in both academic self-efficacy perception of the prospective teacher and their academic motivation levels in terms of department variables. Prospective teachers enrolled at the department of Preschool and Science Education had higher academic self-efficacy perception than those enrolled at the department of Computer Education and Instructional Technologies, English, Special Education, Social Science and Mathematics. Prospective teachers enrolled at the department of Psychological Counseling and Guidance and Science Education had higher academic motivation levels than English prospective teachers. Further, significant positive correlations were observed between academic motivation and academic self-efficacy of prospective teachers.
Aproximaciones a los electores peruanos migrantes y su comportamiento político electoral
Authors: Castillo Cucalón Kristel Karina
Published: November 2018

El voto migrante y el comportamiento del electorado peruano en el exterior es un tema casi nulo en la agenda política en el Perú. El electorado peruano exterior y el voto migrante son analizados con un recuento estadístico agregado; luego con un análisis desagregado de sus resultados por partidos políticos en los tres últimos procesos electorales peruanos. Con las estadísticas sistematizadas, se analiza la lógica del voto migrante desde cuatro criterios de comportamiento electoral. Finalmente, se aborda la cuestión de la circunscripción de peruanos en el exterior dado que es un vacío en el diseño institucional democrático del Perú.
El nuevo camino del sur: las migraciones colombianas hacia Argentina
Authors: Polo Alvis Sebastian , Serrano López Enrique
Published: November 2018

Resumen
A lo largo de los últimos 15 años, las migraciones colombianas al exterior experimentaron una expansión geográfica sin precedentes. Dentro de este fenómeno, se destaca el fortalecimiento de los flujos migratorios hacia países de América Latina, dentro de los que se destaca Argentina. Por lo tanto, el principal objetivo de éste trabajo es estudiar el origen y la evolución de las migraciones colombianas hacia Argentina. A partir de este objetivo, se espera que el lector pueda entender el lugar del objeto central de este trabajo dentro del contexto migratorio argentino, además de comprender tanto las condiciones estadísticas como etnográficas estudiadas en este texto.
Implementation of Hydrogen Solid Solubility Data and Precipitation Threshold Stresses in the Fuel Rod Code TESPA-ROD
Authors: Boldt Felix
Published: November 2018

During operation of light water reactors, the Zircaloy fuel rod cladding is susceptible for hydrogen uptake. When the local solubility limit of hydrogen in Zircaloy is reached, additional hydrogen precipitates as zirconium hydride, which affects the ductility of the fuel rod cladding. Especially, the radially aligned hydrides enhance embrittlement, while circumferential (azimuthal) hydrides have a less detrimental effect. In this work, the influence of high temperatures during the dry storage period on hydride dissolution and precipitation is demonstrated. Therefore, in a descriptive example scenario being discussed, the simulation of a limited heat removal from the cask will heat up the dry storage cask for days and causes dissolution of hydrides in the cladding. Depending on the threshold stress for reorientation, the following cooldown results on different hydride precipitation behavior. The threshold stress leads to an enhanced or delayed precipitation of radial hydrides. The GRS fuel rod code TESPA-ROD is equipped with a new model for hydrogen solubility and applied to long-term storage transients. In this article, hydride refers to zirconium hydrides formed inside the fuel rod cladding.
Phenol-functionalized polymerization control additives for negative tone epoxide crosslinking molecular resists
Authors: Narcross Hannah , Sharp Brandon L. , Ludovice Peter J. , Tolbert Laren M. , Henderson Clifford L.
Published: November 2018

Controlling undesired polymerization in nominally unexposed regions is critical to achieving high-resolution, defect-free patterns when using negative tone molecular resists based on the crosslinking of epoxides. Two onium salt additives, a photodecomposable nucleophile (PDN) and a photoacid generator (PAG), were functionalized with phenols in order to investigate their use as generalized additives capable of slowing crosslinking and improving the resolution of a variety of epoxide resists. Presented here is a phenol-functionalized PDN [tris(4-hydroxyphenyl)sulfonium triflate (TPS-OH-Tf)] and a phenol-functionalized PAG [tris(4-hydroxyphenyl)sulfonium antimonate (TPS-OH-SbF6)] used in combination with a model epoxide resist (4-Ep). Utilizing additives that contained phenols resulted in a decrease in resist sensitivity, but enabled higher additive loadings which could be used to offset this loss in sensitivity. Using TPS-OH-SbF6 did not provide enough polymerization control to prevent line broadening, and the use of TPS-OH-Tf was still required to achieve sub 35 nm 1:1 line:space patterns. Adding TPS-OH-Tf was also found to improve pattern collapse behavior at reduced (<25 nm) feature sizes. Initial patterning using 100 keV electron-beam lithography showed that the resolution of 4-Ep was improved to 15 nm 1:1 line:space patterns using these phenol-functionalized additives and demonstrate the potential of these additives to improve the resolution of a variety of epoxide crosslinking molecular resists.
An analysis of beamforming algorithms for passive bottom reflection-loss estimation
Authors: Muzi Lanfranco , Siderius Martin , Gebbie John
Published: November 2018

This study provides an argument cautioning against the use of adaptive-beamforming (ABF) techniques in conjunction with a known method for estimating the bottom reflection loss from natural marine ambient noise. This application of ABF has been investigated in the past with rather inconsistent results. Furthermore, no formal proof that ABF algorithms do indeed provide an estimate of the bottom reflection loss is available. This study moves from a recent derivation of the relationship between the bottom reflection coefficient and the Fourier transform of the marine-noise spatial coherence function. The circumstances under which the beamforming operation approximates a discrete Fourier transform (DFT) of the spatial coherence function estimated from array data are analyzed. It is shown that, under certain conditions, conventional beamforming is equivalent to directly computing the DFT of the coherence function, as long as some subtle details are properly taken into account. Furthermore, it is shown that ABF cannot be guaranteed, in general, to perform this operation, and therefore provide an estimate of the bottom reflection coefficient. The conclusions are demonstrated on simulated and measured data.
Buying time
Authors: Pennisi Elizabeth
Published: November 2018

In a fast-changing environment, evolution can be too slow. "Plasticity" can give it a chance to catch up
Single-cell multiomics sequencing and analyses of human colorectal cancer
Authors: Bian Shuhui , Hou Yu , Zhou Xin , Li Xianlong , Yong Jun , Wang Yicheng , Wang Wendong , Yan Jia , Hu Boqiang , Guo Hongshan , Wang Jilian , Gao Shuai , Mao Yunuo , Dong Ji , Zhu Ping , Xiu Dianrong , Yan Liying , Wen Lu , Qiao Jie , Tang Fuchou , Fu Wei
Published: November 2018

scTrio-seq identifies colon cancer lineages

To better design treatments for cancer, it is important to understand the heterogeneity in tumors and how this contributes to metastasis. To examine this process, Bian
et al.
used a single-cell triple omics sequencing (scTrio-seq) technique to examine the mutations, transcriptome, and methylome within colorectal cancer tumors and metastases from 10 individual patients. The analysis provided insights into tumor evolution, linked DNA methylation to genetic lineages, and showed that DNA methylation levels are consistent within lineages but can differ substantially among clones.

Science
, this issue p.
1060
Uniaxial pressure control of competing orders in a high-temperature superconductor
Authors: Kim H.-H. , Souliou S. M. , Barber M. E. , Lefrançois E. , Minola M. , Tortora M. , Heid R. , Nandi N. , Borzi R. A. , Garbarino G. , Bosak A. , Porras J. , Loew T. , König M. , Moll P. J. W. , Mackenzie A. P. , Keimer B. , Hicks C. W. , Le Tacon M.
Published: November 2018

Squeezing into the third dimension

Cuprate superconductors are known to harbor charge order in part of their phase diagram. Curiously, the order has a two-dimensional (2D) character at zero magnetic field, whereas a 3D order appears at high fields. Kim
et al.
now show that in a yttrium-based cuprate, a 3D charge order can be induced even at zero magnetic field. The authors compressed the material along one direction and measured a large inelastic x-ray scattering signal that was consistent with the formation of a 3D order. The measurements suggest that the induced order is associated with an optical lattice mode in the material.

Science
, this issue p.
1040
Colonocyte metabolism shapes the gut microbiota
Authors: Litvak Yael , Byndloss Mariana X. , Bäumler Andreas J.
Published: November 2018

Metabolic regulation of microbiota

The gut microbiota affects human health, but we are only just beginning to develop a mechanistic understanding of some of the host-microbe interactions involved. Litvak
et al.
review how host colon epithelial cells mediate the symbiosis. Healthy colonocytes maintain anaerobic conditions in the gut lumen because their metabolism ensures rapid oxygen consumption. Such conditions select for obligate anaerobic organisms. These tend to be those that consume dietary fiber and produce short-chain fatty acids beneficial to the host. If there is a shift in colonocyte metabolism—because of disease, diet, or other damage—the epithelium becomes oxygenated. The presence of oxygen allows expansion of facultative aerobic organisms. Microbes in genera that include pathogens are often oxygen-tolerant, and dysbiosis can be the result.

Science
, this issue p.
eaat9076
The case for monitoring life-span inequality
Authors: van Raalte Alyson A. , Sasson Isaac , Martikainen Pekka
Published: November 2018

Focus on variation in age at death, not just average age
Luminescence and reactivity of a charge-transfer excited iron complex with nanosecond lifetime
Authors: Kjær Kasper Skov , Kaul Nidhi , Prakash Om , Chábera Pavel , Rosemann Nils W. , Honarfar Alireza , Gordivska Olga , Fredin Lisa A. , Bergquist Karl-Erik , Häggström Lennart , Ericsson Tore , Lindh Linnea , Yartsev Arkady , Styring Stenbjörn , Huang Ping , Uhlig Jens , Bendix Jesper , Strand Daniel , Sundström Villy , Persson Petter , Lomoth Reiner , Wärnmark Kenneth
Published: November 2018

Orange-glowing iron at room temperature

Many photoactive coordination compounds contain precious metals. Replacing ruthenium with more–earth-abundant iron has been a long-sought goal, but iron compounds generally relax too rapidly after light absorption to channel the energy productively. Kjær
et al.
prepared an iron compound with an excited state stable enough to emit light for nanoseconds, or that could engage in bimolecular electron transfer (see the Perspective by Young and Oldacre). Targeting a ligand-to-metal rather than metal-to-ligand charge-transfer state was key to the achievement, as was the octahedral coordination environment rigidly enforced by two tridentate carbene ligands.

Science
, this issue p.
249
; see also p.
225
Organic synthesis in a modular robotic system driven by a chemical programming language
Authors: Steiner Sebastian , Wolf Jakob , Glatzel Stefan , Andreou Anna , Granda Jarosław M. , Keenan Graham , Hinkley Trevor , Aragon-Camarasa Gerardo , Kitson Philip J. , Angelone Davide , Cronin Leroy
Published: November 2018

Clear directions for a robotic platform

The chemistry literature contains more than a century's worth of instructions for making molecules, all written by and for humans. Steiner
et al.
developed an autonomous compiler and robotic laboratory platform to synthesize organic compounds on the basis of standardized methods descriptions (see the Perspective by Milo). The platform comprises conventional equipment such as round-bottom flasks, separatory funnels, and a rotary evaporator to maximize its compatibility with extant literature. The authors showcase the system with short syntheses of three common pharmaceuticals that proceeded comparably to manual synthesis.

Science
, this issue p.
eaav2211
; see also p.
122
Induction of Porcine Dermatitis and Nephropathy Syndrome in Piglets by Infection with Porcine Circovirus Type 3
Authors: Jiang Haijun , Wang Dan , Wang Jing , Zhu Shanshan , She Ruiping , Ren Xinxin , Tian Jijing , Quan Rong , Hou Lei , Li Zixuan , Chu Jun , Guo Yuxin , Xi Yanyang , Song Huiqi , Yuan Feng , Wei Li , Liu Jue
Published: November 2018

Porcine circovirus type 3 (PCV3), an emerging porcine circovirus, is considered the cause of porcine dermatitis and nephropathy syndrome (PDNS)-like clinical signs and other systemic diseases in piglets and sows. To evaluate the pathogenesis of PCV3 infection
in vivo
, we used a PCV3 virus stock from the rescue of an infectious PCV3 DNA clone to intranasally inoculate 4- and 8-week-old specific-pathogen-free piglets and demonstrated successful reproduction of PDNS-like disease in animals that were inoculated with PCV3 alone or PCV3 combined with immunostimulation by keyhole limpet hemocyanin. Both 4- and 8-week-old PCV3-inoculated piglets showed similar increases in viral loads in the sera and had seroconverted to PCV3 capsid antibody. Pathological lesions and PCV3-specific antigen were detected in various tissues and organs, while numerous proinflammatory cytokines and chemokines in the sera were significantly upregulated after PCV3 inoculation. These results will provide significant information regarding the pathogenesis of PCV3 in piglets.
Synthesis Approach for Compact VDTA Quadrature Sine-Wave Oscillators with Orthogonal Control
Authors: Li Yong-An
Published: November 2018

From the nodal admittance matrix (NAM) expansion approach and 16 pathological patterns of the voltage differencing transconductance amplifier (VDTA), two different categories, namely sort A and sort B, of the quadrature sine-wave oscillators-employed VDTAs and grounded capacitors in the current mode are synthesized. In all, four quadrature sine-wave oscillators with two sets of quadrature current outputs are attained. Because canonic number is used for component quantity, the oscillators are appropriate to integrated circuit realization and also provide electronic, linear, and orthogonal adjustments between the oscillation criterion and frequency by means of tuning bias currents of the VDTAs. The paper-and-pencil and simulation analyses as well as experimental analysis have been carried out to check the utilized synthesis approach.
D-Map+
Authors: Chen Siming , Chen Shuai , Wang Zhenhuang , Liang Jie , Wu Yadong , Yuan Xiaoru
Published: November 2018

Information diffusion analysis is important in social media. In this work, we present a coherent ego-centric and event-centric model to investigate diffusion patterns and user behaviors. Applying the model, we propose Diffusion Map+ (D-Maps+), a novel visualization method to support exploration and analysis of user behaviors and diffusion patterns through a map metaphor. For ego-centric analysis, users who participated in reposting (i.e., resending a message initially posted by others) one central user’s posts (i.e., a series of original tweets) are collected. Event-centric analysis focuses on multiple central users discussing a specific event, with all the people participating and reposting messages about it. Social media users are mapped to a hexagonal grid based on their behavior similarities and in the chronological order of repostings. With the additional interactions and linkings, D-Map+ is capable of providing visual profiling of influential users, describing their social behaviors and analyzing the evolution of significant events in social media. A comprehensive visual analysis system is developed to support interactive exploration with D-Map+. We evaluate our work with real-world social media data and find interesting patterns among users and events. We also perform evaluations including user studies and expert feedback to certify the capabilities of our method.
Instinctive Assistive Indoor Navigation using Distributed Intelligence
Authors: Muztoba Md , Voleti Rohit , Karabacak Fatih , Park Jaehyun , Ogras Umit Y.
Published: November 2018

Cyber-physical systems (CPS) and the Internet of Things (IoT) offer a significant potential to improve the effectiveness of assistive technologies for those with physical disabilities. Practical assistive technologies should minimize the number of inputs from users to reduce their cognitive and physical effort. This article presents an energy-efficient framework and algorithm for assistive indoor navigation with multi-modal user input. The goal of the proposed framework is to simplify the navigation tasks and make them more instinctive for the user. Our framework automates indoor navigation using only a few user commands captured through a wearable device. The proposed methodology is evaluated using both a virtual smart building and a prototype. The evaluations for three different floorplans show one order of magnitude reduction in user effort and communication energy required for navigation, when compared to conventional navigation methodologies that require continuous user inputs.
InverseCSG
Authors: Du Tao , Inala Jeevana Priya , Pu Yewen , Spielberg Andrew , Schulz Adriana , Rus Daniela , Solar-Lezama Armando , Matusik Wojciech
Published: November 2018

While computer-aided design is a major part of many modern manufacturing pipelines, the design files typically generated describe raw geometry. Lost in this representation is the procedure by which these designs were generated. In this paper, we present a method for reverse-engineering the process by which 3D models may have been generated, in the language of constructive solid geometry (CSG). Observing that CSG is a formal grammar, we formulate this inverse CSG problem as a program synthesis problem. Our solution is an algorithm that couples geometric processing with state-of-the-art program synthesis techniques. In this scheme, geometric processing is used to convert the mixed discrete and continuous domain of CSG trees to a pure discrete domain where modern program synthesizers excel. We demonstrate the efficiency and scalability of our algorithm on several different examples, including those with over 100 primitive parts. We show that our algorithm is able to find simple programs which are close to the ground truth, and demonstrate our method's applicability in mesh re-editing. Finally, we compare our method to prior state-of-the-art. We demonstrate that our algorithm dominates previous methods in terms of resulting CSG compactness and runtime, and can handle far more complex input meshes than any previous method.
3D hair synthesis using volumetric variational autoencoders
Authors: Saito Shunsuke , Hu Liwen , Ma Chongyang , Ibayashi Hikaru , Luo Linjie , Li Hao
Published: November 2018

Recent advances in single-view 3D hair digitization have made the creation of high-quality CG characters scalable and accessible to end-users, enabling new forms of personalized VR and gaming experiences. To handle the complexity and variety of hair structures, most cutting-edge techniques rely on the successful retrieval of a particular hair model from a comprehensive hair database. Not only are the aforementioned data-driven methods storage intensive, but they are also prone to failure for highly unconstrained input images, complicated hairstyles, and failed face detection. Instead of using a large collection of 3D hair models directly, we propose to represent the manifold of 3D hairstyles implicitly through a compact latent space of a volumetric variational autoencoder (VAE). This deep neural network is trained with volumetric orientation field representations of 3D hair models and can synthesize new hairstyles from a compressed code. To enable end-to-end 3D hair inference, we train an additional embedding network to predict the code in the VAE latent space from any input image. Strand-level hairstyles can then be generated from the predicted volumetric representation. Our fully automatic framework does not require any ad-hoc face fitting, intermediate classification and segmentation, or hairstyle database retrieval. Our hair synthesis approach is significantly more robust and can handle a much wider variation of hairstyles than state-of-the-art data-driven hair modeling techniques with challenging inputs, including photos that are low-resolution, overexposured, or contain extreme head poses. The storage requirements are minimal and a 3D hair model can be produced from an image in a second. Our evaluations also show that successful reconstructions are possible from highly stylized cartoon images, non-human subjects, and pictures taken from behind a person. Our approach is particularly well suited for continuous and plausible hair interpolation between very different hairstyles.
MIDAS projection
Authors: Miyashita Leo , Watanabe Yoshihiro , Ishikawa Masatoshi
Published: November 2018

The visual appearance of an object can be disguised by projecting virtual shading as if overwriting the material. However, conventional projection-mapping methods depend on markers on a target or a model of the target shape, which limits the types of targets and the visual quality. In this paper, we focus on the fact that the shading of a virtual material in a virtual scene is mainly characterized by surface normals of the target, and we attempt to realize markerless and modelless projection mapping for material representation. In order to deal with various targets, including static, dynamic, rigid, soft, and fluid objects, without any interference with visible light, we measure surface normals in the infrared region in real time and project material shading with a novel high-speed texturing algorithm in screen space. Our system achieved 500-fps high-speed projection mapping of a uniform material and a tileable-textured material with millisecond-order latency, and it realized dynamic and flexible material representation for unknown objects. We also demonstrated advanced applications and showed the expressive shading performance of our technique.
Layered fields for natural tessellations on surfaces
Authors: Zayer Rhaleb , Mlakar Daniel , Steinberger Markus , Seidel Hans-Peter
Published: November 2018

Mimicking natural tessellation patterns is a fascinating multi-disciplinary problem. Geometric methods aiming at reproducing such partitions on surface meshes are commonly based on the Voronoi model and its variants, and are often faced with challenging issues such as metric estimation, geometric, topological complications, and most critically, parallelization. In this paper, we introduce an alternate model which may be of value for resolving these issues. We drop the assumption that regions need to be separated by lines. Instead, we regard region boundaries as narrow bands and we model the partition as a set of smooth functions layered over the surface. Given an initial set of seeds or regions, the partition emerges as the solution of a time dependent set of partial differential equations describing concurrently evolving fronts on the surface. Our solution does not require geodesic estimation, elaborate numerical solvers, or complicated bookkeeping data structures. The cost per time-iteration is dominated by the multiplication and addition of two sparse matrices. Extension of our approach in a Lloyd's algorithm fashion can be easily achieved and the extraction of the dual mesh can be conveniently preformed in parallel through matrix algebra. As our approach relies mainly on basic linear algebra kernels, it lends itself to efficient implementation on modern graphics hardware.
Practical dynamic facial appearance modeling and acquisition
Authors: Gotardo Paulo , Riviere Jérémy , Bradley Derek , Ghosh Abhijeet , Beeler Thabo
Published: November 2018

We present a method to acquire dynamic properties of facial skin appearance, including dynamic diffuse albedo encoding blood flow, dynamic specular intensity, and per-frame high resolution normal maps for a facial performance sequence. The method reconstructs these maps from a purely passive multi-camera setup, without the need for polarization or requiring temporally multiplexed illumination. Hence, it is very well suited for integration with existing passive systems for facial performance capture. To solve this seemingly underconstrained problem, we demonstrate that albedo dynamics during a facial performance can be modeled as a combination of: (1) a static, high-resolution base albedo map, modeling full skin pigmentation; and (2) a dynamic, one-dimensional component in the CIE L*a*b* color space, which explains changes in hemoglobin concentration due to blood flow. We leverage this albedo subspace and additional constraints on appearance and surface geometry to also estimate specular reflection parameters and resolve high-resolution normal maps with unprecedented detail in a passive capture system. These constraints are built into an inverse rendering framework that minimizes the difference of the rendered face to the captured images, incorporating constraints from multiple views for every texel on the face. The presented method is the first system capable of capturing high-quality dynamic appearance maps at full resolution and video framerates, providing a major step forward in the area of facial appearance acquisition.
Multiple scattering from distributions of specular v-grooves
Authors: Xie Feng , Hanrahan Pat
Published: November 2018

Microfacet-based reflection models are the most common way to represent reflection from rough surfaces. However, a major current limitation of these models is that they only account for single scattering. Unfortunately, single scattering models do not preserve energy. In this paper, we develop a microfacet BRDF for specular v-grooves that includes multiple scattering. Our approach is based on previous work by Zipin, who showed that the number of reflections inside a specular v-groove is bounded and analytically computable. Using his insight, we present a closed form solution for the BRDF and its probability density function (PDF); we also present a method for importance sampling the BRDF. As a result, our BRDF can be easily used within a path-traced rendering system such as PBRT. The model supports any microfacet distribution function, and spatially-varying surface roughness. The images produced by the model have a pleasing appearance compared to traditional single-scattering models.
Invertible grayscale
Authors: Xia Menghan , Liu Xueting , Wong Tien-Tsin
Published: November 2018

Once a color image is converted to grayscale, it is a common belief that the original color cannot be fully restored, even with the state-of-the-art colorization methods. In this paper, we propose an innovative method to synthesize
invertible grayscale.
It is a grayscale image that can fully restore its original color. The key idea here is to encode the original color information into the synthesized grayscale, in a way that users cannot recognize any anomalies. We propose to learn and embed the color-encoding scheme via a convolutional neural network (CNN). It consists of an encoding network to convert a color image to grayscale, and a decoding network to invert the grayscale to color. We then design a loss function to ensure the trained network possesses three required properties: (a) color invertibility, (b) grayscale conformity, and (c) resistance to quantization error. We have conducted intensive quantitative experiments and user studies over a large amount of color images to validate the proposed method. Regardless of the genre and content of the color input, convincing results are obtained in all cases.
Image smoothing via unsupervised learning
Authors: Fan Qingnan , Yang Jiaolong , Wipf David , Chen Baoquan , Tong Xin
Published: November 2018

Image smoothing represents a fundamental component of many disparate computer vision and graphics applications. In this paper, we present a unified unsupervised (label-free) learning framework that facilitates generating flexible and high-quality smoothing effects by directly learning from data using deep convolutional neural networks (CNNs). The heart of the design is the training signal as a novel energy function that includes an edge-preserving regularizer which helps maintain important yet potentially vulnerable image structures, and a spatially-adaptive

L
p

flattening criterion which imposes different forms of regularization onto different image regions for better smoothing quality. We implement a diverse set of image smoothing solutions employing the unified framework targeting various applications such as, image abstraction, pencil sketching, detail enhancement, texture removal and content-aware image manipulation, and obtain results comparable with or better than previous methods. Moreover, our method is extremely fast with a modern GPU (e.g, 200 fps for 1280×720 images).
Deep blending for free-viewpoint image-based rendering
Authors: Hedman Peter , Philip Julien , Price True , Frahm Jan-Michael , Drettakis George , Brostow Gabriel
Published: November 2018

Free-viewpoint image-based rendering (IBR) is a standing challenge. IBR methods combine warped versions of input photos to synthesize a novel view. The image quality of this combination is directly affected by geometric inaccuracies of multi-view stereo (MVS) reconstruction and by view- and image-dependent effects that produce artifacts when contributions from different input views are blended. We present a new deep learning approach to blending for IBR, in which we use held-out real image data to learn blending weights to combine input photo contributions. Our Deep Blending method requires us to address several challenges to achieve our goal of interactive free-viewpoint IBR navigation. We first need to provide sufficiently accurate geometry so the Convolutional Neural Network (CNN) can succeed in finding correct blending weights. We do this by combining two different MVS reconstructions with complementary accuracy vs. completeness tradeoffs. To tightly integrate learning in an interactive IBR system, we need to adapt our rendering algorithm to produce a fixed number of input layers that can then be blended by the CNN. We generate training data with a variety of captured scenes, using each input photo as ground truth in a held-out approach. We also design the network architecture and the training loss to provide high quality novel view synthesis, while reducing temporal flickering artifacts. Our results demonstrate free-viewpoint IBR in a wide variety of scenes, clearly surpassing previous methods in visual quality, especially when moving far from the input cameras.
LookinGood
Authors: Martin-Brualla Ricardo , Pandey Rohit , Yang Shuoran , Pidlypenskyi Pavel , Taylor Jonathan , Valentin Julien , Khamis Sameh , Davidson Philip , Tkach Anastasia , Lincoln Peter , Kowdle Adarsh , Rhemann Christoph , Goldman Dan B , Keskin Cem , Seitz Steve , Izadi Shahram , Fanello Sean
Published: November 2018

Motivated by augmented and virtual reality applications such as telepresence, there has been a recent focus in
real-time
performance capture of humans under motion. However, given the real-time constraint, these systems often suffer from artifacts in geometry and texture such as holes and noise in the final rendering, poor lighting, and low-resolution textures. We take the novel approach to augment such real-time performance capture systems with a deep architecture that takes a rendering from an arbitrary viewpoint, and jointly performs completion, super resolution, and denoising of the imagery in real-time. We call this approach
neural (re-)rendering
, and our live system "LookinGood". Our deep architecture is trained to produce high resolution and high quality images from a coarse rendering in real-time. First, we propose a self-supervised training method that does not require manual ground-truth annotation. We contribute a specialized reconstruction error that uses semantic information to focus on relevant parts of the subject, e.g. the face. We also introduce a
salient reweighing scheme
of the loss function that is able to discard outliers. We specifically design the system for virtual and augmented reality headsets where the consistency between the left and right eye plays a crucial role in the final user experience. Finally, we generate temporally stable results by explicitly minimizing the difference between two consecutive frames. We tested the proposed system in two different scenarios: one involving a single RGB-D sensor, and upper body reconstruction of an actor, the second consisting of full body 360° capture. Through extensive experimentation, we demonstrate how our system generalizes across unseen sequences and subjects.
Monte Carlo convolution for learning on non-uniformly sampled point clouds
Authors: Hermosilla Pedro , Ritschel Tobias , Vázquez Pere-Pau , Vinacua Àlvar , Ropinski Timo
Published: November 2018

Deep learning systems extensively use convolution operations to process input data. Though convolution is clearly defined for structured data such as 2D images or 3D volumes, this is not true for other data types such as sparse point clouds. Previous techniques have developed approximations to convolutions for restricted conditions. Unfortunately, their applicability is limited and cannot be used for general point clouds. We propose an efficient and effective method to learn convolutions for non-uniformly sampled point clouds, as they are obtained with modern acquisition techniques. Learning is enabled by four key novelties: first, representing the convolution kernel itself as a multilayer perceptron; second, phrasing convolution as a Monte Carlo integration problem, third, using this notion to combine information from multiple samplings at different levels; and fourth using Poisson disk sampling as a scalable means of hierarchical point cloud learning. The key idea across all these contributions is to guarantee adequate consideration of the underlying non-uniform sample distribution function from a Monte Carlo perspective. To make the proposed concepts applicable to real-world tasks, we furthermore propose an efficient implementation which significantly reduces the GPU memory required during the training process. By employing our method in hierarchical network architectures we can outperform most of the state-of-the-art networks on established point cloud segmentation, classification and normal estimation benchmarks. Furthermore, in contrast to most existing approaches, we also demonstrate the robustness of our method with respect to sampling variations, even when training with uniformly sampled data only. To support the direct application of these concepts, we provide a ready-to-use TensorFlow implementation of these layers at https://github.com/viscom-ulm/MCCNN.
ECF-Type ATP-Binding Cassette Transporters
Authors: Rempel S. , Stanek W.K. , Slotboom D.J.
Published: November 2018

Energy-coupling factor (ECF)–type ATP-binding cassette (ABC) transporters catalyze membrane transport of micronutrients in prokaryotes. Crystal structures and biochemical characterization have revealed that ECF transporters are mechanistically distinct from other ABC transport systems. Notably, ECF transporters make use of small integral membrane subunits (S-components) that are predicted to topple over in the membrane when carrying the bound substrate from the extracellular side of the bilayer to the cytosol. Here, we review the phylogenetic diversity of ECF transporters as well as recent structural and biochemical advancements that have led to the postulation of conceptually different mechanistic models. These models can be described as power stroke and thermal ratchet. Structural data indicate that the lipid composition and bilayer structure are likely to have great impact on the transport function. We argue that study of ECF transporters could lead to generic insight into membrane protein structure, dynamics, and interaction.
Handling Missing Data in Instrumental Variable Methods for Causal Inference
Authors: Kennedy Edward H. , Mauro Jacqueline A. , Daniels Michael J. , Burns Natalie , Small Dylan S.
Published: November 2018

In instrumental variable studies, missing instrument data are very common. For example, in the Wisconsin Longitudinal Study, one can use genotype data as a Mendelian randomization–style instrument, but this information is often missing when subjects do not contribute saliva samples or when the genotyping platform output is ambiguous. Here we review missing at random assumptions one can use to identify instrumental variable causal effects, and discuss various approaches for estimation and inference. We consider likelihood-based methods, regression and weighting estimators, and doubly robust estimators. The likelihood-based methods yield the most precise inference and are optimal under the model assumptions, while the doubly robust estimators can attain the nonparametric efficiency bound while allowing flexible nonparametric estimation of nuisance functions (e.g., instrument propensity scores). The regression and weighting estimators can sometimes be easiest to describe and implement. Our main contribution is an extensive review of this wide array of estimators under varied missing-at-random assumptions, along with discussion of asymptotic properties and inferential tools. We also implement many of the estimators in an analysis of the Wisconsin Longitudinal Study, to study effects of impaired cognitive functioning on depression.
Moderate aging does not exacerbate cisplatin-induced kidney injury or fibrosis despite altered inflammatory cytokine expression and immune cell infiltration
Authors: Sharp Cierra N. , Doll Mark , Dupre Tess V. , Beverly Levi J. , Siskind Leah J.
Published: November 2018

Aging is a risk factor for certain forms of kidney injury due to normal physiological changes, but the role of aging in cisplatin-induced kidney injury is not well defined in humans or animal models of the disease. To improve on current knowledge in this field, we treated 8- and 40-wk-old FVB/n mice with one high dose of cisplatin as a model of acute kidney injury or with repeated low doses of cisplatin (7 mg/kg cisplatin once a week for 4 wk) as a clinically relevant model of chronic kidney disease to determine if aging exacerbates cisplatin-induced kidney injury. Levels of acute kidney injury were comparable in 8- and 40-wk-old mice. In 40-wk-old mice, fibrotic markers were elevated basally, but treatment with cisplatin did not exacerbate fibrosis. We concluded that this may be the result of a decreased inflammatory response in 40-wk-old cisplatin-treated mice compared with 8-wk-old mice. Despite a decreased inflammatory response, the level of immune cell infiltration was greater in 40-wk-old cisplatin-treated mice than 8-wk-old mice. Our data highlight the importance of examining age as a risk factor for cisplatin-induced kidney injury.