bluuebunny/crossref_metadata_2025_split huggingface dataset:
Remarkable population structure in the tropical Atlantic lace corals Stylaster roseus (Pallas, 1766) and Stylaster blatteus (Boschma, 1961)
Authors: Gnecco Mariana , Nunes Flávia L. D. , González-Zapata Fanny L. , Dueñas Luisa F. , Zilberberg Carla , Lindner Alberto , Sánchez Juan A. 
Published: November 2022

AbstractBiodiversity on coral reefs depends not only on primary reef-builders, but also on associated taxa that create microhabitats for other species. Hydrocorals of the genusStylaster, commonly known as lace corals, form small branching colonies that enhance three-dimensional complexity on reefs and are known to support a variety of commensal species. Furthermore, the genus is highly speciose, further increasing biodiversity. Despite their important ecological roles, little is known about the evolutionary history and the intraspecific diversity and structure in these broadly distributed hydrocorals. Here, we assessed the phylogenetic relationships among Atlantic species in the genusStylasterand examined the genetic structure ofS. roseusin the Tropical Western Atlantic (Caribbean and Brazil) and ofS. blatteusin the Tropical Eastern Atlantic (Africa), using DNA sequences from the 16S ribosomal gene. Time-calibrated phylogenetic analyses showed thatS. roseusandS. blatteusdiverged at ~ 24.6 Ma. A well-supported Brazilian clade withinS. roseusindicates a possible cryptic species that diverged at ~ 11.6 Ma, consistent with the formation of the Amazon River at 9 Ma (Hoorn et al. in Glob Planet Change 153:51–65, 2017). Strong genetic structure was observed even over moderate distances, with ΦSTvalues over all populations being 0.98 forS. roseusand 0.90 forS. blatteus. Nearly, all haplotypes were private (found in a single location) and diverged by many mutational steps from one another. In contrast, genetic diversity was low at the local scale for both species, with most sites showing no variation (a single haplotype). These results are coherent with the reproductive strategy of Stylasteridae, where larvae are brooded and are highly developed at the time of release, often settling near the parental colony. Limited dispersal coupled with possible clonal reproduction have likely contributed to the high levels of genetic differentiation observed here. Lace corals show unusual reproductive and population dynamics compared to other reef inhabiting cnidarians. Future work may reveal additional cryptic diversity in this poorly studied family.
A MWCNTs-COOH/PSS nanocomposite–modified screen-printed electrode for the determination of synthetic phenolic antioxidants by HPLC with amperometric detection
Authors: Abad-Gil Lucía , García-Ríos Mayte , Isabel-Cabrera Carmen , Gismera M. Jesús , Sevilla M. Teresa , Procopio Jesús R. 
Published: November 2022

AbstractNew sensing platforms based on screen-printed carbon electrodes modified with composites based on polystyrene sulfonate and oxidized multi-walled carbon nanotubes (PSS/MWCNTs-COOH/SPCE) have been used to develop a novel HPLC method with electrochemical detection (ECD) for the determination of the most used synthetic phenolic antioxidants in cosmetics: butylhydroxytoluene (BHT), butylhydroxyanisole (BHA), tert-butylhydroquinone (TBHQ) and propyl gallate (PG). Optimal separation conditions were achieved using methanol: 0.10 mol L−1 acetate solution at pH 6 as mobile phase with a gradient elution program from 60 to 90% of methanol percentage in 15 min. The electrochemical detection was carried out in amperometric mode using the PSS/MWCNTs-COOH/SPCE at + 0.80 V vs. Ag. Under these optimal separation and detection conditions, the limits of detection (LOD) were between 0.11 and 0.25 mg L−1. These LOD values were better, especially for BHT, than those previously published in other HPLC methods. Linear ranges from 0.37 mg L−1, 0.83 mg L−1, 0.69 mg L−1 and 0.56 mg L−1 to 10 mg L−1 were obtained for PG, TBHQ, BHA and BHT, respectively. RSD values equal or lower than 5% and 8% were achieved for repeatability and reproducibility, respectively. The HPLC-ECD method was successfully applied to analyze different cosmetic samples. Recovery values within 83–109% were obtained in the validation studies.
Graphical Abstract
Pathogenesis and current therapies for non-infectious uveitis
Authors: Wu Xue , Tao Mengying , Zhu Ling , Zhang Ting , Zhang Ming 
Published: November 2022

AbstractNon-infectious uveitis (NIU) is a disorder with various etiologies and is characterized by eye inflammation, mainly affecting people of working age. An accurate diagnosis of NIU is crucial for appropriate therapy. The aim of therapy is to improve vision, relieve ocular inflammation, prevent relapse, and avoid treatment side effects. At present, corticosteroids are the mainstay of topical or systemic therapy. However, repeated injections are required for the treatment of chronic NIU. Recently, new drug delivery systems that may ensure intraocular delivery of therapeutic drug levels have been highlighted. Furthermore, with the development of immunosuppressants and biologics, specific therapies can be selected based on the needs of each patient. Immunosuppressants used in the treatment of NIU include calcineurin inhibitors and antimetabolites. However, systemic immunosuppressive therapy itself is associated with adverse effects due to the inhibition of immune function. In patients with refractory NIU or those who cannot tolerate corticosteroids and immunosuppressors, biologics have emerged as alternative treatments. Thus, to improve the prognosis of patients with NIU, NIU should be managed with different drugs according to the response to treatment and possible side effects.
On the potential of undifferenced and uncombined GNSS time and frequency transfer with integer ambiguity resolution and satellite clocks estimated
Authors: Mi Xiaolong , Zhang Baocheng , El-Mowafy Ahmed , Wang Kan , Yuan Yunbin 
Published: November 2022

AbstractThe use of global navigation satellite systems (GNSS) has been a competitive way to provide high-precision and low-cost time and frequency transfer results. However, the traditional GNSS method, the precise point positioning (PPP), is usually based on the ionosphere-free (IF) combination, which is not flexible when applying multi-frequency scenarios. In addition, PPP relies on precise satellite clock products with an accuracy of tens of picoseconds, limiting the time and frequency transfer performance. More importantly, achieving integer ambiguity resolution (IAR) is challenging, which makes high-precision phase observations underutilized. To achieve a better time transfer performance, we must consider all those factors from the GNSS end. In this contribution, a new GNSS time and frequency model at the undifferenced and uncombined (UDUC) level is first derived. In the UDUC model, the satellite clocks are estimated together with other parameters, and the integer ambiguities are resolved in the double-differenced (DD) form for their reliable estimation. Our numerical tests suggest three major findings. First, with integer ambiguities resolved, the UDUC model with satellite clocks fixed showed a 20% to 50% improvement compared with the UDUC PPP model. Second, with IAR and satellite clocks estimated, the proposed UDUC model shows a 10%–40% improvement over the model with satellite clocks fixed. Third, with integer ambiguities resolved and satellite clocks estimated, GPS, Galileo, and BDS-3 all have the potential to achieve frequency transfer in the low-mid $$10^{ - 17}$$

10

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17

range for averaging times within one day.
The method of forced probabilities: a computation trick for Bayesian model evidence
Authors: Banerjee Ishani , Walter Peter , Guthke Anneli , Mumford Kevin G. , Nowak Wolfgang 
Published: November 2022

AbstractBayesian model selection objectively ranks competing models by computing Bayesian Model Evidence (BME) against test data. BME is the likelihood of data to occur under each model, averaged over uncertain parameters. Computing BME can be problematic: exact analytical solutions require strong assumptions; mathematical approximations (information criteria) are often strongly biased; assumption-free numerical methods (like Monte Carlo) are computationally impossible if the data set is large, for example like high-resolution snapshots from experimental movies. To use BME as ranking criterion in such cases, we develop the “Method of Forced Probabilities (MFP)”. MFP swaps the direction of evaluation: instead of comparing thousands of model runs on random model realizations with the observed movie snapshots, we force models to reproduce the data in each time step and record the individual probabilities of the model following these exact transitions. MFP is fast and accurate for models that fulfil the Markov property in time, paired with high-quality data sets that resolve all individual events. We demonstrate our approach on stochastic macro-invasion percolation models that simulate gas migration in porous media, and list additional examples of probable applications. The corresponding experimental movie was obtained from slow gas injection into water-saturated, homogeneous sand in a 25 x 25 x 1 cm acrylic glass tank. Despite the movie not always satisfying the high demands (resolving all individual events), we can apply MFP by suggesting a few workarounds. Results confirm that the proposed method can compute BME in previously unfeasible scenarios, facilitating a ranking among competing model versions for future model improvement.
Projection Based Semi-Implicit Partitioned Reduced Basis Method for Fluid-Structure Interaction Problems
Authors: Nonino Monica , Ballarin Francesco , Rozza Gianluigi , Maday Yvon 
Published: November 2022

AbstractIn this manuscript a POD-Galerkin based Reduced Order Model for unsteady Fluid-Structure Interaction problems is presented. The model is based on a partitioned algorithm, with semi-implicit treatment of the coupling conditions. A Chorin–Temam projection scheme is applied to the incompressible Navier–Stokes problem, and a Robin coupling condition is used for the coupling between the fluid and the solid. The coupled problem is based on an Arbitrary Lagrangian Eulerian formulation, and the Proper Orthogonal Decomposition procedure is used for the generation of the reduced basis. We extend existing works on a segregated Reduced Order Model for Fluid-Structure Interaction to unsteady problems that couple an incompressible, Newtonian fluid with a linear elastic solid, in two spatial dimensions. We consider three test cases to assess the overall capabilities of the method: an unsteady, non-parametrized problem, a problem that presents a geometrical parametrization of the solid domain, and finally, a problem where a parametrization of the solid’s shear modulus is taken into account.
Bayesian learning via neural Schrödinger–Föllmer flows
Authors: Vargas Francisco , Ovsianas Andrius , Fernandes David , Girolami Mark , Lawrence Neil D. , Nüsken Nikolas 
Published: November 2022

AbstractIn this work we explore a new framework for approximate Bayesian inference in large datasets based on stochastic control. We advocate stochastic control as a finite time and low variance alternative to popular steady-state methods such as stochastic gradient Langevin dynamics. Furthermore, we discuss and adapt the existing theoretical guarantees of this framework and establish connections to already existing VI routines in SDE-based models.
Nephrotoxic effect of heavy metals and the role of DNA repair gene among secondary aluminum smelter workers
Authors: Moubarz Gehan , Mohammed Atef M. F. , Saleh Inas A. , Shahy Eman M. , Helmy Mona A. 
Published: November 2022

Abstract
This study aims to estimate the association between some heavy metals in suspended particulate matter (SPM) and kidney damage among workers at different departments in a secondary aluminum production plant. It also investigates the association between Xeroderma Pigmentosum complementation group D (XPD) gene polymorphisms and worker’s susceptibility to kidney dysfunction. It was conducted on 30 workers from the administrative departments and 147 workers from different departments in the production line. Estimation of some heavy metals (Al, Co, Ni, Cu, Pb, and Cd) in suspended particulate matter (SPM) is done. Also, urinary levels of those metals were measured for all workers. Kidney injury molecule 1 (KIM-1), clusterin levels, and XPD protein level were estimated. Genotyping of XPD gene polymorphisms was performed. The measured annual average concentrations of the estimated heavy metals were lower than the permissible limits. Gravity area had the maximum concentration of metals with a higher Al average daily dose and hazardous index > 1. Kidney injury biomarkers (clusterin and KIM-1) were increased significantly (p < 0.05) while XPD protein showed the lowest levels among workers at the gravity and cold rolling areas. XPD Asn/Asp genotype was more dominant among those workers (85.7%). Conclusion: aluminum workers are at risk of kidney disorders due to heavy metal exposure. The individual’s susceptibility to the diseases is related to the DNA repair efficiency mechanisms. The defect in XPD protein represents a good indicator of susceptibility to the disease. KIM-1 and clusterin estimation is a predictor biomarker for early-staged kidney diseases.
Selection of the most sensitive configuration of strip array detectors for x-ray beam monitoring in radiotherapy of cancer utilizing singular value decomposition
Authors: Högele Wolfgang , Zygmanski Piotr 
Published: November 2022

AbstractWe propose a concise mathematical framework in order to compare detector configurations efficiently for x-ray beam monitoring in radiotherapy of cancer. This framework consists of the singular value decomposition (SVD) of the system matrix and the definition of an effective information threshold based on the relative error inequality utilizing the condition number of a matrix. The goal of this paper is to present the mathematical argument as well as to demonstrate its use for modeling the best detector configuration for monitoring x-ray beams in external beam therapy. This analysis depends neither on specific measurements of a given set of x-ray beams, nor does it depend in specific reconstruction algorithms of the beam shape, and therefore represents a configuration meta-analysis. In the results section, we compare three possible detector designs, each leading to a highly underdetermined system, and are able to determine their effective information content relative to each other. Furthermore, by changing design parameters, such as the geometric detector configuration, number of detectors, detector pixel size, and the x-ray beam blur, deeper insight in this challenging inverse problem is achieved and the most sensitive monitoring scheme is determined.
What divides Salafis: how local realities overwrite grand typologies in Cambodia’s Salafi movement
Authors: Pall Zoltan 
Published: November 2022

AbstractQuintan Wiktorowicz’s typology and other methods of classification developed by other scholars from his approach have been the most popular when studying Salafism. However, such typologies, especially when examining Salafism in non-Middle Eastern and minority contexts, have their shortcomings. The first main problem with current typologies is that they discuss distinct Salafi factions at a specific time and local context, but intend to be universal. However, these factions often tend not to be conceptually different, as in many cases, their participants only behave differently due to different circumstances in different localities. Second, these typologies were devised by scholars who chiefly study the Middle East and distinguish different Salafi groups based on their discourses on issues often relevant only in Middle Eastern contexts. This article tests the applicability of the existing classifications of Salafism by drawing on three ethnographic case studies from Cambodia. In Cambodia, Salafism emerged in a Muslim minority context. With the expansion of its networks, fragmentation occurred within the movement due to disagreements such as how to deal with the Muslim (non-Salafi) other and the non-Muslim majority. The article argues that classifications should be set up based on observing local group dynamics instead of being universal. This is because differences among Salafis, just as in other social movements, mainly arise due to the participants’ interaction with the local realities and issues.
Resilient und überstabil. Zur Krisenfestigkeit der Europäischen Union
Authors: Immerfall Stefan 
Published: November 2022

ZusammenfassungDie Europäischen Gemeinschaften der Nachkriegsjahre haben sich trotz mannigfacher Krisen zu einem stabilen Gebilde entwickelt. Diese Entwicklung war durchaus erwartungswidrig. Der Artikel betont die zentrale Rolle politischer, juridischer und institutioneller Pfadabhängigkeiten im Europäischen Integrationsprozess. Die Kernthese lautet im Anschluss daran, dass die Europäische Union mittlerweile als geradezu überstabil bezeichnet werden muss, da einmal getroffene Weichenstellungen aus strukturellen Gründen kaum mehr korrigiert werden können. Die EU muss daher Alternativen zum Grundsatz der Einheitlichkeit entwickeln und Wege finden, ihren Kritikern innerhalb des Gemeinschaftssystems eine Stimme zu geben. Krisenresistenz, so das Fazit, könnte sich sonst paradoxerweise als Achillesferse der Integration erweisen.
„Diego ist tot, es lebe Diego!“ – Soziologische Beobachtungen zur ungebrochenen Popularität Maradonas in Argentinien
Authors: Kühnle Felix , Reinold Marcel 
Published: November 2022

ZusammenfassungIm November 2020 starb Diego Armando Maradona. Das öffentliche Trauergeschehen und die Kommunikation in Reaktion auf seinen Tod verdeutlichen den außerordentlichen Symbolwert Maradonas in Argentinien auf besondere Weise. Betrachtet man jedoch die Vielzahl an Eskapaden, Regelverstößen, Gesetzesbrüchen und sonstigen Grenzüberschreitungen Maradonas, erscheinen seine fast ungebrochene Popularität und regelrecht sakrale Überhöhung zu Lebzeiten und über den Tod hinaus in einem anderen Licht. Neben seinen beiden Dopingfällen, Schlägereien auf dem Fußballplatz oder obszönen Gesten gegen sportliche Kontrahenten ist gerade auch die Liste seiner außersportlichen Verfehlungen lang. Erklärungsbedürftig ist dabei nicht nur, wie Maradona trotz aller Skandale Held bleiben konnte, sondern auch, in welchem Maße die Widersprüche, Ambivalenzen und Unzulänglichkeiten seinen Heldenstatus erst erzeugten. Aus diesem Grund werden im vorliegenden Beitrag die Leitsemantiken, Legitimationsrhetoriken, Neutralisierungstechniken, Rechtfertigungsgeschichten und sonstigen Präfigurationen identifiziert, die im allgemeinen Reden über Maradona wiederkehrend auftauchen. Es wird gezeigt, wie Gemeinschaftsfiktionen, Protestsymbole, Geniekonzept, Opfernarrative und Gottessemantik seinen Heldenstatus kommunikativ immunisieren, kontrafaktisch stabilisieren und zusätzlich befördern.
Super-Solidus Hot Isostatic Pressing Heat Treatments for Advanced Single Crystal Ni-Base Superalloys
Authors: Lopez-Galilea Inmaculada , Hecker Lisa , Epishin Alexander , Bürger David , Ruttert Benjamin , Thome Pascal , Weber Sebastian , Theisen Werner 
Published: November 2022

Abstract
Super-solidus hot isostatic pressing (SSHIP) heat treatment has first been developed and applied to the third-generation Ni-base single crystal superalloy CMSX-10 K. This new type of heat treatment aims at significantly reducing the total time required for the solution heat treatment and at enhancing mechanical properties as compared to conventional heat treatment routes. The SSHIP is an innovative, economical and sustainable approach that can be applied to all types of Ni-base SX superalloys. It is especially interesting for alloys with a high content of refractory elements and a large volume fraction of eutectic microstructure in the as-cast state.
Kinetic Study on Reduction of FeO in a Molten HIsarna Slag by Various Solid Carbon Sources
Authors: Htet Theint Theint , Yan Zhiming , Khasraw Darbaz , Hage Johannes , Meijer Koen , Li Zushu 
Published: November 2022

Abstract
To investigate the reduction behaviour of different reductants such as charcoal (CC), thermal coal (TC), and carbon black (CB) with HIsarna slag, a series of isothermal reduction experiments were performed in a vertical tube resistance furnace (VTF), coupled with a Quadrupole mass spectrometer (QMS) at 1450 °C, 1475 °C and 1500 °C. The results confirm that the highest overall reduction rate was achieved by CC, followed by TC and CB. The reduction mechanism between FeO containing molten slag and the selected carbonaceous materials is determined by studying the morphology of the water quenched samples at the intervals of 1.5, 3 and 5 minutes, using optical and scanning electron microscopes. The results reveal that the overall reaction is controlled by two main mechanisms: (1) nucleation and growth of CO bubbles, proceeded by the gaseous intermediates CO and CO2; and (2) diffusion of FeO in the molten slag. The initial reduction period in which chemical reaction control is dominant, can be described by the Avrami–Erofeev model, whereas the final period is described by the three-dimensional diffusion model.
Automatic diagnosis of late-life depression by 3D convolutional neural networks and cross-sample Entropy analysis from resting-state fMRI
Authors: Lin Chemin , Lee Shwu-Hua , Huang Chih-Mao , Chen Guan-Yen , Chang Wei , Liu Ho-Ling , Ng Shu-Hang , Lee Tatia Mei-Chun , Wu Shun-Chi 
Published: November 2022

AbstractResting-state fMRI has been widely used in investigating the pathophysiology of late-life depression (LLD). Unlike the conventional linear approach, cross-sample entropy (CSE) analysis shows the nonlinear property in fMRI signals between brain regions. Moreover, recent advances in deep learning, such as convolutional neural networks (CNNs), provide a timely application for understanding LLD. Accurate and prompt diagnosis is essential in LLD; hence, this study aimed to combine CNN and CSE analysis to discriminate LLD patients and non-depressed comparison older adults based on brain resting-state fMRI signals. Seventy-seven older adults, including 49 patients and 28 comparison older adults, were included for fMRI scans. Three-dimensional CSEs with volumes corresponding to 90 seed regions of interest of each participant were developed and fed into models for disease classification and depression severity prediction. We obtained a diagnostic accuracy > 85% in the superior frontal gyrus (left dorsolateral and right orbital parts), left insula, and right middle occipital gyrus. With a mean root-mean-square error (RMSE) of 2.41, three separate models were required to predict depressive symptoms in the severe, moderate, and mild depression groups. The CSE volumes in the left inferior parietal lobule, left parahippocampal gyrus, and left postcentral gyrus performed best in each respective model. Combined complexity analysis and deep learning algorithms can classify patients with LLD from comparison older adults and predict symptom severity based on fMRI data. Such application can be utilized in precision medicine for disease detection and symptom monitoring in LLD.