bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiregion segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks
Authors: Dolz Jose , Xu Xiaopan , Rony Jérôme , Yuan Jing , Liu Yang , Granger Eric , Desrosiers Christian , Zhang Xi , Ben Ayed Ismail , Lu Hongbing 
Published: October 2018

PurposePrecise segmentation of bladder walls and tumor regions is an essential step toward noninvasive identification of tumor stage and grade, which is critical for treatment decision and prognosis of patients with bladder cancer (BC). However, the automatic delineation of bladder walls and tumor in magnetic resonance images (MRI) is a challenging task, due to important bladder shape variations, strong intensity inhomogeneity in urine, and very high variability across the population, particularly on tumors’ appearance. To tackle these issues, we propose to leverage the representation capacity of deep fully convolutional neural networks.MethodsThe proposed network includes dilated convolutions to increase the receptive field without incurring extra cost or degrading its performance. Furthermore, we introduce progressive dilations in each convolutional block, thereby enabling extensive receptive fields without the need for large dilation rates. The proposed network is evaluated on 3.0T T2‐weighted MRI scans from 60 pathologically confirmed patients with BC.ResultsExperiments show the proposed model to achieve a higher level of accuracy than state‐of‐the‐art methods, with a mean Dice similarity coefficient of 0.98, 0.84, and 0.69 for inner wall, outer wall, and tumor region segmentation, respectively. These results represent a strong agreement with reference contours and an increase in performance compared to existing methods. In addition, inference times are less than a second for a whole three‐dimensional (3D) volume, which is between two and three orders of magnitude faster than related state‐of‐the‐art methods for this application.ConclusionWe showed that a CNN can yield precise segmentation of bladder walls and tumors in BC patients on MRI. The whole segmentation process is fully automatic and yields results similar to the reference standard, demonstrating the viability of deep learning models for the automatic multiregion segmentation of bladder cancer MRI images.
Expression of β‐NGF and high‐affinity NGF receptor (TrKA) in llama (Lama glama) male reproductive tract and spermatozoa
Authors: Sari Luciana M. , Zampini Renato , Argañaraz Martin E. , Carretero María I. , Fumuso Fernanda G. , Barraza Daniela E. , Ratto Marcelo , Apichela Silvana A. 
Published: October 2018

Abstractβ‐Nerve growth factor (β‐NGF) is a seminal plasma element, responsible for inducing ovulation in camelids. The main organ of β‐NGF production remains nondescript. The aims of this study were to (a) characterize gene expression and protein localization of β‐NGF and its main receptor tyrosine kinase receptor A (TrKA) in the llama male reproductive tract, and (b) determine whether the seminal β‐NGF interacts with ejaculated sperm by localizing β‐NGF and TrKA in epididymal, ejaculated, and acrosome‐reacted (AR) sperms and, additionally, by identifying β‐NGF presence in sperm‐adsorbed proteins (SAP). Both β‐NGF and TrkA transcripts are widely expressed along the male reproductive tract, with a higher expression level of β‐NGF at prostate (p < 0.05). β‐NGF immunolabeling was only positive for prostate, whereas TrKA label was present in epithelial and muscular cells of testis, prostate, bulbourethral glands, and epididymis. Using an immunofluorescent technique, β‐NGF was colocalized with TrKA in the middle piece of ejaculated and AR sperm. However, only TrKA was observed in epididymal sperm indicating that β‐NGF could have a seminal origin. This was also confirmed by the identification of four β‐NGF isoforms in SAP. This study extends the knowledge about the participation of β‐NGF/TrkA in llama reproduction, providing evidence that may have roles in the regulation of sperm physiology.
Experimental study of particle migration in polymer processing
Authors: Colón Quintana José Luis , Heckner Tobias , Chrupala Achim , Pollock Jesse , Goris Sebastian , Osswald Tim 
Published: October 2018

Extrusion and injection molding processes of filled polymers are widely used in industry due to their high strength‐to‐weight ratios and for their ability to manufacture a variety of geometries while improving the overall mechanical and thermal properties. However, filler migration and filler–matrix separation during processing are phenomena that are not fully understood. To gain an improved understanding of these phenomena, polypropylene samples with different glass bead concentrations were manufactured using extrusion, injection molding and a customized screwless extruder that was built in‐house. Computed tomography was performed on the samples to observe particle position and distribution after material solidification.For all three processes, filler migration and filler–matrix separation was observed. In the extrusion and screwless extrusion processes, particles migrated towards the wall, contrary to current theories and believes. During the injection molding process, filler–matrix separation was manifested as bead‐free zones in the center region and the walls of the spiral mold at the entrance region of the spiral mold. These bead‐free zones were later filled at the far end of the spiral mold suggesting migration of particles along flow with almost no bead‐free zones at the end of the mold. Particle redistribution towards the wall and the center during flow could possibly have happened due to migration and fountain flow effects. POLYM. COMPOS., 40:2165–2177, 2019. © 2018 Society of Plastics Engineers
Prognosis for pregnancies with trisomy 16 confined to the placenta: A Danish cohort study
Authors: Grau Madsen Sandra , Uldbjerg Niels , Sunde Lone , Becher Naja ,   The Danish Fetal Medicine Study Group,   The Danish Clinical Genetics Study Group
Published: October 2018

AbstractObjectiveTo evaluate the risk of adverse pregnancy outcome when trisomy 16 confined to the placenta is diagnosed and to identify possible prognostic markers for adverse outcomes in these pregnancies.MethodRegistered cases (n = 49) of trisomy 16 diagnosed prenatally in Denmark from 1990 to 2013 were included.ResultsTwenty‐five of the pregnancies intended to be continued had confined placental trisomy 16 mosaicism (CPM16). Adverse pregnancy outcome was seen in 17 CPM16 pregnancies (68%), ranging from mild small for gestational age (SGA) to fetal malformations and intrauterine demise. For cases ascertained by combined first trimester screening, the median concentration of pregnancy associated plasma protein A (PAPP‐A) was 0.17 MoM (IQR: 0.11 MoM). Adverse pregnancy outcome showed a trend toward an association with a high frequency of trisomic cells. Eight children (32%) were born at term with a normal birth weight and no malformations.ConclusionThe risk of adverse pregnancy outcome in case of CPM16 is correlated to ascertainment by combined first trimester screening and tends to be associated with a high frequency of trisomic cells in the placenta. We recommend that variables including ascertainment, the frequency of trisomic cells, and the maternal serum concentration of PAPP‐A are taken into consideration when evaluating the prognosis in CPM16 while acknowledging that these factors are strongly correlated.
Self‐assembly of amphiphilic ABA random triblock copolymers in water
Authors: Kozawa Susan K. , Matsumoto Kazuma , Suzuki Ayaka , Sawamoto Mitsuo , Terashima Takaya 
Published: October 2018

ABSTRACTSelf‐assembly of amphiphilic ABA random triblock copolymers in water serves as a novel approach to create unique structure micelles connected with flexible linkages. The ABA triblock copolymers consist of amphiphilic random copolymers bearing hydrophilic poly(ethylene glycol) and hydrophobic dodecyl pendants as the A segments and a hydrophilic poly(ethylene oxide) (PEO) as the middle B segment. The A block is varied in dodecyl methacrylate content of 20%–50% and degree of polymerization (DP) of 100‐200. By controlling the composition and DP of the A block, various architectures can be tailor‐made as micelles in water: PEO‐linked double core unimer micelles, PEO‐looped unimer or dimer micelles, and multichain micelles. Those PEO‐linked or looped micelles further exhibit thermoresponsive solubility in water. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2019, 57, 313–321
Conjugated Carbazole‐Based Schiff Bases as Photoinitiators: From Facile Synthesis to Efficient Two‐Photon Polymerization
Authors: Li Zhiquan , Hu Peng , Zhu Junzhe , Gao Yajun , Xiong Xiang , Liu Ren 
Published: October 2018

ABSTRACTExploration of simple and economical synthetic routes to construct active two‐photon initiators (2PIs) with long conjugation length is highly desirable to promote the development of two‐photon‐induced photopolymerization technology. In this article, several conjugated carbazole‐based derivatives containing N=C bonds as π bridges and electron donor/acceptor groups were prepared through one‐step Schiff base reaction. The structure–activity relationship was systematically investigated through calculations and experimental tests. The results showed that compared to the D‐π‐D‐π‐D molecules, the A‐π‐D‐π‐A molecules exhibited stronger charge transfer, which induce redshifted linear absorption and enhanced two‐photon absorption at 800 nm. The 2PIs displayed aggregation‐induced emission property and show potential for the fabrication of luminescent microdevices. In two‐photon‐induced microfabrication tests, the formulations containing novel 2PIs exhibited lower threshold energy than the widely used commercial photoinitiator Irgacure 369 and the two‐photon resists IP‐L is the brand name of the two‐photon resist from Nanoscribe, specially designed for nanoscribe's laser lithography systems. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2018, 56, 2692–2700
Migration patterns of parents, children and siblings: Evidence for patrilocality in contemporary Finland
Authors: Ghosh Asim , Berg Venla , Bhattacharya Kunal , Monsivais Daniel , Kertesz Janos , Kaski Kimmo , Rotkirch Anna 
Published: October 2018

AbstractFamily members are known to serve as geographical attractors in migration, yet evidence for sex‐biased family migration in developed societies is mixed. We investigate gender differences in migration of family members in Finland. Using the FinnFamily register data set (N = 60,000 index individuals and their close kin), we explore family coresidence and migration within the 19 administrative regions of Finland in 1970–2012. We study the propensity for regional migration by gender and age, the likelihood for children to reside in the same region as their parents and to reunite after migration to different regions, and whether siblings function as regional attractors. Finland experienced intense regional migration to the capital area during the study period. Individual migration propensity peaked at infancy and at 18–28 years. Throughout their lives, most Finns live in the same region as their family members: over 65% with parents, over 55% with full sibling(s), and over 50% with half sibling(s). Siblings are likely to migrate to the same region, and having more siblings strengthens this attraction. Results also indicate some degree of patrilocality. Daughters migrate earlier and with higher rates than sons, whereas sons are at any age more likely to live in the same region as their parents. The propensity for adult brothers to live in the same region is also higher than for other sibling pairs. Family members serve as important geographical attractors to each other through the life course in contemporary Finland, and this is more pronounced for males than for females.
Cervical consistency index and risk of Cesarean delivery after induction of labor at term
Authors: Migliorelli F. , Rueda C. , Angeles M. A. , Baños N. , Posadas D. E. , Gratacós E. , Palacio M. 
Published: October 2018

ABSTRACTObjectiveTo evaluate the association between the cervical consistency index (CCI) and the risk of Cesarean delivery after planned induction of labor (IOL) at term.MethodsThis was a prospective observational study of women with a term singleton pregnancy admitted for IOL due to maternal or fetal indication. Ultrasonographic images were obtained before IOL and CCI was calculated offline once recruitment was completed. The main outcome was defined as Cesarean delivery due to failed IOL or arrest of labor. Cesarean deliveries indicated due to maternal or fetal compromise (Van Dillen's grade 1 or 2) were excluded from analysis. Univariate statistical analysis was performed using Fisher's exact test and Student's t‐test for categorical and continuous variables, respectively. Multivariate analysis was performed using logistic regression, including CCI and other variables related to the main outcome. Intraclass correlation coefficients were used to estimate intra‐ and interobserver agreement.ResultsOf 510 women admitted for IOL during the study period and for whom image quality was adequate, 46 were excluded due to emergency Cesarean delivery leaving 464 pregnancies for analysis. Cesarean section due to failed IOL or arrest of labor was performed in 100/464 (21.6%) pregnancies. The mean CCI of women who underwent Cesarean delivery was not significantly different from that in those who had vaginal delivery after IOL (70.1 ± 12.3% vs 70.0 ± 13.1%; P = 0.94). Multivariate analysis also showed absence of statistical association between CCI and Cesarean delivery for failed IOL or arrest of labor. Intraclass correlation coefficients for intra‐ and interobserver agreement were 0.81 (95% CI, 0.66–0.89) and 0.86 (95% CI, 0.75–0.92), respectively.ConclusionCCI does not seem to be associated with the risk of Cesarean delivery after IOL. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.
Methodological considerations for interpreting the Language Familiarity Effect in talker processing
Authors: Levi Susannah V. 
Published: October 2018

The Language Familiarity Effect (LFE)—where listeners are better at processing talker‐voice information in their native language than in an unfamiliar language—has received renewed attention in the past 10 years. Numerous studies have sought to probe the underlying causes of this advantage by cleverly manipulating aspects of the stimuli (using phonologically related languages, backwards speech, nonwords) and by examining individual differences across listeners (testing reading ability and pitch perception). Most of these studies find evidence for the importance of phonological information or phonological processing as a supporting mechanism for the LFE. What has not been carefully examined, however, are how other methodological considerations such as task effects and stimulus length can change performance on talker‐voice processing tasks. In this review, I provide an overview of the literature on the LFE and examine how methodological decisions affect the presence or absence of the LFE.This article is categorized under:

Linguistics > Language in Mind and Brain
Psychology > Language
Empirical Bayes methods in variable selection
Authors: Bar Haim , Liu Kangyan 
Published: October 2018

The emergence of technologies that produce massive amounts of data such as gene sequencing and distributed sensor systems, created an urgent need to develop statistical methodologies and computational tools to deal with Big Data. Linear regression, which is arguably among the most commonly used inferential tools in statistics, was not designed with Big Data applications in mind. Modern applications in which the number of predictors is often in the thousands, and may even be in the millions, renders the traditional solution to regression analysis, useless. Thus, before any regression analysis can be done, it is necessary to begin with “variable selection”. The goal of any good variable selection algorithm is to select only the variables which are useful in predicting the outcome. At the same time, such algorithms have to be computationally efficient. The empirical Bayes approach provides a sound statistical framework for developing variable selection methods. Empirical Bayes allows to “borrow strength” across predictors, thus increasing the power to detect significant ones, while controlling the false discovery rate. While the modeling approach is Bayesian, the crucial step in the empirical Bayes approach replaces the potentially cumbersome and slow integration via Monte Carlo simulations with a simple approximation to the posterior distribution of the regression coefficients.This article is categorized under:Statistical Models > Bayesian Models
NUTs and bolts beyond Lovelock
Authors: Bueno Pablo , Cano Pablo A. , Hennigar Robie A. , Mann Robert B. 
Published: October 2018

AbstractWe construct a plethora of new Euclidean AdS-Taub-NUT and bolt solutions of several four- and six-dimensional higher-curvature theories of gravity with various base spaces ℬ. InD= 4, we consider Einsteinian cubic gravity, for which we construct solutions with$$ \mathrm{\mathcal{B}}={\mathbb{S}}^2,{\mathbb{T}}^2 $$ℬ=S2,T2. These represent the first generalizations of the Einstein gravity Taub-NUT/bolt solutions for any higher-curvature theory in four dimensions. InD= 6, we show that no new solutions are allowed for any Generalized quasi-topological gravity at cubic order. They exist however when we consider quartic Quasi-topological and Generalized quasi-topological terms, for which we construct new solutions with$$ \mathrm{\mathcal{B}}=\mathbb{C}{\mathrm{\mathbb{P}}}^2,{\mathbb{S}}^2 \times {\mathbb{S}}^2,{\mathbb{S}}^2\times {\mathbb{T}}^2,{\mathbb{T}}^2\times {\mathbb{T}}^2 $$ℬ=ℂℙ2,S2×S2,S2×T2,T2×T2. In all cases, the solutions are characterized by a single metric function, and they reduce to the corresponding ones in Einstein gravity when the higher-curvature couplings are set to zero. While the explicit profiles must be constructed numerically (except for a few cases), we obtain fully analytic expressions for the thermodynamic properties of all solutions. The new solutions present important differences with respect to Einstein gravity, including regular bolts for arbitrary values of the NUT charge, critical points, and re-entrant phase transitions.
Laser line triangulation for fast 3D measurements on large gears
Authors: Auerswald Matthias Marcus , von Freyberg Axel , Fischer Andreas 
Published: October 2018

AbstractThe causes of geometrical deviations from the production process and the prediction of application properties, such as noise behavior, wear or material fatigue, are only possible by having detailed information about the gear geometry. The gold standard for the gear quality inspection is represented by dimensional measurements with a tactile sensor system. As a result for industrial applications, the slow serial measurement leads to the compromise of a random inspection of the gear geometry. For the purpose of a faster and more extensive surface acquisition, a laser line triangulation sensor is investigated providing 1280 points at a line width of 25 mm with up to 200 lines/s. The results at the tooth of a large cylindrical involute gear with a pitch circle diameter of 922 mm and a face width of 246 mm show the qualification for fast three-dimensional measurements of the convex and reflective surface. The detection of the complete profile line at once is possible. It is shown that the measurement deviation of laser line triangulation can be minimized by increasing the dynamic threshold. The measurement deviations amount to ± 8.2 µm and can be attributed to random and systematic errors. Compared to the standard gear inspection, an acceleration factor of 5700 was attained. An optical scanning of the complete tooth flank provides the prerequisite for an identification of surface defects in the form of breakouts and blemish.
Laplace approximation and natural gradient for Gaussian process regression with heteroscedastic student-t model
Authors: Hartmann Marcelo , Vanhatalo Jarno 
Published: October 2018

AbstractWe propose the Laplace method to derive approximate inference for Gaussian process (GP) regression in the location and scale parameters of the student-$$ {t}$$tprobabilistic model. This allows both mean and variance of data to vary as a function of covariates with the attractive feature that the student-$$ {t}$$tmodel has been widely used as a useful tool for robustifying data analysis. The challenge in the approximate inference for the model, lies in the analytical intractability of the posterior distribution and the lack of concavity of the log-likelihood function. We present the natural gradient adaptation for the estimation process which primarily relies on the property that the student-$$ {t}$$tmodel naturally has orthogonal parametrization. Due to this particular property of the model the Laplace approximation becomes significantly more robust than the traditional approach using Newton’s methods. We also introduce an alternative Laplace approximation by using model’s Fisher information matrix. According to experiments this alternative approximation provides very similar posterior approximations and predictive performance to the traditional Laplace approximation with model’s Hessian matrix. However, the proposed Laplace–Fisher approximation is faster and more stable to calculate compared to the traditional Laplace approximation. We also compare both of these Laplace approximations with the Markov chain Monte Carlo (MCMC) method. We discuss how our approach can, in general, improve the inference algorithm in cases where the probabilistic model assumed for the data is not log-concave.
Knowledge of consequences: an explanation of the epistemic side-effect effect
Authors: Paprzycka-Hausman Katarzyna 
Published: October 2018

AbstractThe Knobe effect (Analysis 63(3):190–194, 2003a) consists in our tendency to attribute intentionality to bringing about a side effect when it is morally bad but not when it is morally good. Beebe and Buckwalter (Mind Lang 25:474–498, 2010) have demonstrated that there is an epistemic side-effect effect (ESEE): people are more inclined to attribute knowledge when the side effect is bad in Knobe-type cases. ESEE is quite robust. In this paper, I present a new explanation of ESEE. I argue that when people attribute knowledge in morally negative cases, they express a consequence-knowledge claim (knowledge that a possible consequence of an action is that harm will occur) rather than a predictive claim (knowledge that harm will actually occur). I use the omissions account (Paprzycka in Mind Lang 30(5):550–571, 2015) to explain why the consequence-knowledge claim is particularly salient in morally negative cases. Unlike the doxastic heuristic account (Alfano et al. in Monist 95(2):264–289, 2012), the omissions account can explain the persistence of ESEE in the so-called slight-chance of harm conditions. I present the results of empirical studies that test the predictions of the account. I show that ESEE occurs in Butler-type scenarios. Some of the studies involve close replications of Nadelhoffer’s (Analysis 64(3):277–284, 2004) study.