bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial heterogeneity and driving factors of aerosol in Western China: Analysis on multiangle implementation of atmospheric correction–aerosol optical depth in Xinjiang over 2001–2019
Authors: Ma Wen , Ding Jianli , Jin Xiaoye
Published: December 2022

Knowledge of aerosol dynamics is essential to combating atmospheric aerosol pollution, and there is a growing interest in aerosol changes and their drivers. However, the effects of interactions between natural and anthropogenic drivers of aerosol are not well understood. Here, we analyse changes in aerosol optical depth (AOD) in Xinjiang, China using the multiangle implementation of atmospheric correction aerosol products over 2001–2019 and investigate the driving factors of aerosol dynamics using a random forest (RF) and a geographical detector. The results show the dominant AOD changes in the quasi‐period of 3.21 months, 7.86 months, 1.19 years, for seasonal, half‐year, and interannual variations of aerosols. The increasing and then decreasing nonlinear trends were observed in the interannual AOD variation during 19 years period. The importance ranking results of the two models indicated that meteorological factors dominated the spatial distribution of AOD in Xinjiang (72.73% for RF and 65.78% for the geographic detector), and that interactions between factors enhanced the explanatory power in AOD changes. In addition, the influence of anthropogenic factors on AOD was increasing in North Xinjiang, and the influence of precipitation and population on AOD was increasing in East Xinjiang. However, the influence of drivers on AOD in South Xinjiang was basically constant over time, showing the spatially heterogeneous relationship between AOD and drivers. This study emphasized the spatial heterogeneity and driving factors of small‐scale aerosols in arid regions and so can guide targeted air pollution prevention and control in local areas.
Continuity properties of the shearlet transform and the shearlet synthesis operator on the Lizorkin type spaces
Authors: Bartolucci Francesca , Pilipović Stevan , Teofanov Nenad
Published: December 2022

We develop a distributional framework for the shearlet transform and the shearlet synthesis operator , where is the Lizorkin test function space and is the space of highly localized test functions on the standard shearlet group . These spaces and their duals are called Lizorkin type spaces of test functions and distributions. We analyze the continuity properties of these transforms when the admissible vector ψ belongs to . Then, we define the shearlet transform and the shearlet synthesis operator of Lizorkin type distributions as transpose mappings of the shearlet synthesis operator and the shearlet transform, respectively. They yield continuous mappings from to and from to . Furthermore, we show the consistency of our definition with the shearlet transform defined by direct evaluation of a distribution on the shearlets. The same can be done for the shearlet synthesis operator. Finally, we give a reconstruction formula for Lizorkin type distributions, from which follows that the action of such generalized functions can be written as an absolutely convergent integral over the standard shearlet group.
Analysis of carbohydrates and glycoconjugates by matrix‐assisted laser desorption/ionization mass spectrometry: An update for 2019–2020
Authors: Harvey David J.
Published: December 2022

This review is the tenth update of the original article published in 1999 on the application of matrix‐assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo‐ and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.
Characterizing viral samples using machine learning for Raman and absorption spectroscopy
Authors: Boodaghidizaji Miad , Milind Athalye Shreya , Thakur Sukirt , Esmaili Ehsan , Verma Mohit S. , Ardekani Arezoo M.
Published: December 2022

Machine learning methods can be used as robust techniques to provide invaluable information for analyzing biological samples in pharmaceutical industries, such as predicting the concentration of viral particles of interest in biological samples. Here, we utilized both convolutional neural networks (CNNs) and random forests (RFs) to predict the concentration of the samples containing measles, mumps, rubella, and varicella‐zoster viruses (ProQuad®) based on Raman and absorption spectroscopy. We prepared Raman and absorption spectra data sets with known concentration values, then used the Raman and absorption signals individually and together to train RFs and CNNs. We demonstrated that both RFs and CNNs can make predictions with R2 values as high as 95%. We proposed two different networks to jointly use the Raman and absorption spectra, where our results demonstrated that concatenating the Raman and absorption data increases the prediction accuracy compared to using either Raman or absorption spectrum alone. Additionally, we further verified the advantage of using joint Raman‐absorption with principal component analysis. Furthermore, our method can be extended to characterize properties other than concentration, such as the type of viral particles.
Measuring the effects of information exchange on incentives to collude using calibrated simulations (with an example of the South African oil industry)
Authors: Bageri Vasiliki , Katsoulacos Yannis
Published: December 2022

Information sharing may help firms solve the coordination and monitoring problems that threaten the sustainability of concerted practices or tacit collusion. This paper models the impact of information sharing on the incentives of firms in an oligopolistic market to sustain a concerted practice, taking into account recent theoretical developments and empirical evidence on tacit collusion. We then calibrate and simulate the effect of information sharing, mediated by the industry association, on each firm in the South African oil industry. Our analysis offers a rigorous, but also practical, framework for facilitating Competition Authorities' decision making in investigations of information sharing.
Stochastically‐induced dynamics of earthquakes
Authors: Makoveeva Eugenya V. , Tsvetkov Ivan N. , Ryashko Lev B.
Published: December 2022

Motivated by an important geophysical application, we analyze the nonlinear dynamics of the number of earthquakes per unit time in a given Earth's surface area. At first, we consider a dynamical model of earthquakes describing their rhythmic behavior with time delays. This model comprises different earthquake scenarios divided into three types (A, B, and C) accordingly to various system dynamics. We show that the deterministic system contains stable equilibria and a limit cycle whose size drastically depends on the production rate
of earthquakes and their time delay effect. As this takes place, the frequency of earthquakes possesses an oscillatory behavior dependent on
. To study the role of
in more detail, we have introduced a white Gaussian noise in the governing equation. First of all, we have shown that the dynamical system is stochastically excitable, that is, it excites larger‐amplitude noise‐induced fluctuations in the frequency of earthquakes. In addition, these large‐amplitude stochastic fluctuations can alternate with small‐amplitude fluctuations over time. In other words, the frequency of earthquakes can change its amplitude in an irregular manner under the influence of white noise. Another important effect is how close the current value of
is to its bifurcation point. The closer this value is, the less noise generates large‐amplitude fluctuations in the earthquake frequency.
An untrained deep learning method for reconstructing dynamic MR images from accelerated model‐based data
Authors: Slavkova Kalina P. , DiCarlo Julie C. , Wadhwa Viraj , Kumar Sidharth , Wu Chengyue , Virostko John , Yankeelov Thomas E. , Tamir Jonathan I.
Published: December 2022

Purpose

To implement physics‐based regularization as a stopping condition in tuning an untrained deep neural network for reconstructing MR images from accelerated data.

Methods

The ConvDecoder (CD) neural network was trained with a physics‐based regularization term incorporating the spoiled gradient echo equation that describes variable‐flip angle data. Fully‐sampled variable‐flip angle k‐space data were retrospectively accelerated by factors of R = {8, 12, 18, 36} and reconstructed with CD, CD with the proposed regularization (CD + r), locally low‐rank (LR) reconstruction, and compressed sensing with L1‐wavelet regularization (L1). Final images from CD + r training were evaluated at the “argmin” of the regularization loss; whereas the CD, LR, and L1 reconstructions were chosen optimally based on ground truth data. The performance measures used were the normalized RMS error, the concordance correlation coefficient, and the structural similarity index.

Results

The CD + r reconstructions, chosen using the stopping condition, yielded structural similarity indexs that were similar to the CD (p = 0.47) and LR structural similarity indexs (p = 0.95) across R and that were significantly higher than the L1 structural similarity indexs (p = 0.04). The concordance correlation coefficient values for the CD + r T1 maps across all R and subjects were greater than those corresponding to the L1 (p = 0.15) and LR (p = 0.13) T1 maps, respectively. For R ≥ 12 (≤4.2 min scan time), L1 and LR T1 maps exhibit a loss of spatially refined details compared to CD + r.

Conclusion

The use of an untrained neural network together with a physics‐based regularization loss shows promise as a measure for determining the optimal stopping point in training without relying on fully‐sampled ground truth data.
Red cell exchange transfusions increase cerebral capillary transit times and may alter oxygen extraction in sickle cell disease
Authors: DeBeer Tonner , Jordan Lori C. , Waddle Spencer , Lee Chelsea , Patel Niral J. , Garza Maria , Davis Taylor , Pruthi Sumit , Jones Sky , Donahue Manus J.
Published: December 2022

Persons with sickle cell disease (SCD) suffer from chronic hemolytic anemia, reduced blood oxygen content, and lifelong risk of silent and overt stroke. Major conventional stroke risk factors are absent in most individuals with SCD, yet nearly 50% have evidence of brain infarcts by the age of 30 years, indicating alternative etiologies for ischemia. We investigated whether radiological evidence of accelerated blood water transit through capillaries, visible on arterial spin labeling (ASL) magnetic resonance imaging, reduces following transfusion‐induced increases in hemoglobin and relates to oxygen extraction fraction (OEF). Neurological evaluation along with anatomical and hemodynamic imaging with cerebral blood flow (CBF)‐weighted pseudocontinuous ASL and OEF imaging with T2‐relaxation‐under‐spin‐tagging were applied in sequence before and after blood transfusion therapy (n = 32) and in a comparator cohort of nontransfused SCD participants on hydroxyurea therapy scanned at two time points to assess stability without interim intervention (n = 13). OEF was calculated separately using models derived from human hemoglobin‐F, hemoglobin‐A, and hemoglobin‐S. Gray matter CBF and dural sinus signal, indicative of rapid blood transit, were evaluated at each time point and compared with OEF using paired statistical tests (significance: two‐sided p < 0.05). No significant change in sinus signal was observed in nontransfused participants (p = 0.650), but a reduction was observed in transfused participants (p = 0.034), consistent with slower red cell transit following transfusion. The dural sinus signal intensity was inversely associated with OEF pretransfusion (p = 0.011), but not posttransfusion. Study findings suggest that transfusion‐induced increases in total hemoglobin may lengthen blood transit times through cerebral capillaries and alter cerebral OEF in SCD.
Application of a global–local full‐waveform inversion of Rayleigh wave to estimate the near‐surface shear wave velocity model
Authors: Lamuraglia Salvatore , Stucchi Eusebio , Aleardi Mattia
Published: December 2022

We present a global–local full‐waveform inversion (FWI) of surface waves to estimate a high‐resolution shear wave velocity model of the near‐surface at the site of Grenoble (France). The seismic data we use have been acquired in the framework of the InterPACIFIC project. A first attempt is made by employing the multichannel analysis of surface waves (MASW) to invert the fundamental modes of Rayleigh waves. This inversion is solved through a global optimization driven by the neighbourhood algorithm. However, the limiting 1D assumption, together with the severely ill‐posedness of the MASW inversion motivate us to exploit all the information content of the recorded Rayleigh waves (i.e., travel‐times and amplitudes) by implementing a global–local FWI approach. We first perform a global FWI in which a genetic algorithm (GA) is used to minimize the L2 norm difference between observed and simulated seismic waveforms up to 30 Hz. This inversion employs a two‐grid scheme in which the subsurface is described by a fine grid input to the forward modelling, whereas the unknowns are defined on a coarse grid. A bilinear interpolation brings the coarse‐grid model into the fine grid. To accelerate the convergence, two strategies are considered; offset marching and frequency marching. Then, the long‐wavelength velocity profile provided by the GA inversion is used as the starting point for a local FWI for further refinement of the predicted model. In this case, we employ a frequency‐marching strategy up to a maximum frequency of 60 Hz. Both the global and local approaches use a finite difference code for the forward computation. Despite the limited a priori information infused into the inversion framework, the presented global–local FWI scheme provides reliable results as demonstrated by the good match between recorded and predicted seismograms and by the agreement of the estimated velocity with both nearby borehole data and stratigraphic information on the study site. Our global–local strategy also achieves better data fitting and improved matching with the available borehole data with respect to the velocity profile estimated when the local FWI is started from the MASW predictions.
The impact of microfinance on poverty reduction in Vietnam: A dynamic panel‐data analysis
Authors: Duong Hoai A. , Nghiem Hong S.
Published: December 2022

The current study uses the Generalised Method of Moments to examine the dynamic relationship between access to microfinance and poverty reduction. The panel‐data set is constructed from the Vietnam Household Living Standard Surveys during 2002–2008. The results show that access to microfinance in the previous period significantly improves per adult‐equivalent income and consumption of the households in the current period. However, previous participation in microfinance programs is not sufficient to help households escape from poverty. In addition, both private and government bank loans significantly help improve household per adult‐equivalent income, consumption, and poverty rates. The empirical results imply that a larger loan size, diversified loans for different consumption purposes, and improvement in infrastructure and facilities, especially in rural areas, are believed to help reduce poverty.
Isotopic labeling of metabolic water with 18O2
Authors: Koch George W. , Schwartz Egbert
Published: December 2022

Rationale

Water is the medium of life, is involved in biochemical reactions, and is exchanged among internal pools and with the water in the external environment of organisms. Understanding these processes can be improved by isotopically labeling the metabolic water that is produced inside the cells of organisms during aerobic respiration.

Methods

Here we describe a new method for isotopically labeling cellular water by incubating microbes and plant tissues in air enriched in 18O2. As oxygen gas is reduced during respiration, H218O is produced. The rate of H218O production and the synthesis of biomolecules that incorporate 18O from H218O can be quantified using cavity ringdown spectrometry and isotope ratio mass spectrometry.

Results

For Escherichia coli in solution culture, soil microbial communities, and respiring tissues of plants, the amount of H218O produced was strongly correlated with that of 18O2 consumed during incubations. Measurements of 18O in DNA, microbial biomass, and CO2 showed that metabolic water was an important substrate in biosynthesis reactions.

Conclusions

Any organism with aerobic respiration is amenable to labeling with 18O2, and the method described here enables a new approach to investigate questions regarding plant and microbial physiology. In plants, 18O introduced as metabolic water could be tracked as it moves between living cells and exchanges with external water. For probing soil microbial physiology, the method described here has the advantage over the application of exogenous H218O of not increasing the soil moisture, a disturbance that can affect microbial metabolism.
Investigating scientific modeling practices in U.S. and German elementary science classrooms: A comparative, cross‐national video study
Authors: Böschl Florian , Forbes Cory , Lange‐Schubert Kim
Published: December 2022

Science education reform efforts have emphasized the incorporation of more authentic and meaningful scientific practices into formal learning environments. With this focus on practices, such as scientific modeling, a powerful tool for sense‐making and reasoning, comes a need to observe and understand if and how it is actually occurring, particularly in elementary science learning environments. To address this need, and moving forward an international, collaborative research effort centered around scientific modeling, we undertook a cross‐national observational study in which we used an observation protocol to characterize scientific modeling practices in elementary classrooms in both the United States and Germany. Drawing on existing video‐based datasets from multiple projects, this study's findings provide empirical evidence for model‐based teaching and learning and explore the relative frequencies of relevant modeling subpractices (i.e., construction, use, evaluation, and revision of scientific models) in regular, day‐to‐day elementary science classrooms. This study also illustrates the differences and similarities between German and American science instruction. In general, students in both countries experience model construction more often than other modeling practices. German teachers more consistently foreground anchoring phenomena and students’ questions/preconceptions as part of the modeling process, thus leading to slightly higher overall modeling scores—despite a complete lack of model evaluation and revision in any of the observed German classrooms. Ultimately, however, young learners in both nations seem to experience alarmingly little opportunities to engage in any of the modeling subpractices. Particularly in terms of modeling as a means to make sense of phenomena, constrained by teachers most commonly using finished representations (i.e., models) of phenomena and processes to teach science/deliver content. Our results indicate the need for a greater focus on all scientific modeling subprocesses, particularly the integration of scientific modeling with already established, more general (e.g., inquiry‐based) strategies for effective science teaching and an emphasis on actualizing modeling as an authentic sense‐making endeavor.
Game of tax: Rethinking the relationship between redistribution and reciprocity through a Georgian tax lottery
Authors: Björklund Larsen Lotta
Published: December 2022

This article addresses a failed tax lottery in the country of Georgia's rapid yet shaky political and economic development. The purpose of a tax lottery is to formalize transactions and increase tax compliance. It aims to motivate consumers in any commercial transaction to ask for a receipt qua lottery ticket and ensure that businesses pay taxes due. Tax lotteries thus have a dual function: more revenue is collected from businesses, and consumers do soft policing work while also having a chance to win. Taxation and gambling are two very different ways of exchanging. Gambling is mostly voluntary, effortless, and playful, whereas taxation is dull government revenue collection. Yet both gambling and taxation are ways to understand any society and its political life through its reciprocal qualities and redistributive effects. Drawing on anthropological research studying taxation and gambling, this article is a Schumpeterian analysis, as it provides an inlet into how Georgians regard their society. Studying this tax lottery provides an opportunity to rethink the relation between redistribution and reciprocity, and I argue that to understand how citizens accept the redistribution of taxation, we have to attend to its reciprocal qualities.
Exsolution of Ru Nanoparticles on BaCe0.9Y0.1O3‐δ Modifying Geometry and Electronic Structure of Ru for Ammonia Synthesis Reaction Under Mild Conditions
Authors: Kim Hayoung , Jan Asif , Kwon Deok‐Hwang , Ji Ho‐Il , Yoon Kyung Joong , Lee Jong‐Ho , Jun Yongseok , Son Ji‐Won , Yang Sungeun
Published: December 2022

Green ammonia is an efficient, carbon‐free energy carrier and storage medium. The ammonia synthesis using green hydrogen requires an active catalyst that operates under mild conditions. The catalytic activity can be promoted by controlling the geometry and electronic structure of the active species. An exsolution process is implemented to improve catalytic activity by modulating the geometry and electronic structure of Ru. Ru nanoparticles exsolved on a BaCe0.9Y0.1O3‐δ support exhibit uniform size distribution, 5.03 ± 0.91 nm, and exhibited one of the highest activities, 387.31 mmolNH3 gRu−1 h−1 (0.1 MPa and 450 °C). The role of the exsolution and BaCe0.9Y0.1O3‐δ support is studied by comparing the catalyst with control samples and in‐depth characterizations. The optimal nanoparticle size is maintained during the reaction, as the Ru nanoparticles prepared by exsolution are well‐anchored to the support with in‐plane epitaxy. The electronic structure of Ru is modified by unexpected in situ Ba promoter accumulation around the base of the Ru nanoparticles.
Robust Full‐Spectral Color Tuning of Photonic Colloids
Authors: Dodero Andrea , Djeghdi Kenza , Bauernfeind Viola , Airoldi Martino , Wilts Bodo D. , Weder Christoph , Steiner Ullrich , Gunkel Ilja
Published: December 2022

Creation of color through photonic morphologies manufactured by molecular self‐assembly is a promising approach, but the complexity and lack of robustness of the fabrication processes have limited their technical exploitation. Here, it is shown that photonic spheres with full‐color tuning across the entire visible spectrum can be readily and reliably achieved by the emulsification of solutions containing a block copolymer (BCP) and two swelling additives. Solvent diffusion out of the emulsion droplets gives rise to 20–150 µm‐sized spheres with an onion‐like lamellar morphology. Controlling the lamellar thickness by differential swelling with the two additives enables color tuning of the Bragg interference‐based reflection band across the entire visible spectrum. By studying five different systems, a set of important principles for manufacturing photonic colloids is established. Two swelling additives are required, one of which must exhibit strong interactions with one of the BCP blocks. The additives should be chosen to enhance the dielectric contrast, and the formation kinetics of the spheres must be sufficiently slow to enable the emergence of the photonic morphology. The proposed approach is versatile and robust and allows the scalable production of photonic pigments with possible future applications in inks for cosmetics and arts, coatings, and displays.
Scalable Fabrication of MXene‐PVDF Nanocomposite Triboelectric Fibers via Thermal Drawing
Authors: Hasan Md Mehdi , Sadeque Md Sazid Bin , Albasar Ilgın , Pecenek Hilal , Dokan Fatma Kilic , Onses M. Serdar , Ordu Mustafa
Published: December 2022

In the data‐driven world, textile is a valuable resource for improving the quality of life through continuous monitoring of daily activities and physiological signals of humans. Triboelectric nanogenerators (TENG) are an attractive option for self‐powered sensor development by coupling energy harvesting and sensing ability. In this study, to the best of the knowledge, scalable fabrication of Ti3C2Tx MXene‐embedded polyvinylidene fluoride (PVDF) nanocomposite fiber using a thermal drawing process is presented for the first time. The output open circuit voltage and short circuit current show 53% and 58% improvement, respectively, compared to pristine PVDF fiber. The synergistic interaction between the surface termination groups of MXene and polar PVDF polymer enhances the performance of the fiber. The flexibility of the fiber enables the weaving of fabric TENG devices for large‐area applications. The fabric TENG (3 × 2 cm2) demonstrates a power density of 40.8 mW m−2 at the matching load of 8 MΩ by maintaining a stable performance over 12 000 cycles. Moreover, the fabric TENG has shown the capability of energy harvesting by operating a digital clock and a calculator. A distributed self‐powered sensor for human activities and walking pattern monitoring are demonstrated with the fabric.
Insights into the Importance of Native Passivation Layer and Interface Reactivity of Metallic Lithium by Electrochemical Impedance Spectroscopy
Authors: Srout Mohammed , Carboni Marco , Gonzalez Jose‐Antonio , Trabesinger Sigita
Published: December 2022

Lithium‐metal batteries offer substantial advantages over lithium‐ion batteries in terms of gravimetric and volumetric energy densities. However, their widespread practical use is hindered by safety concerns, often attributed to the poor stability of the metallic lithium interface, where electrochemical impedance spectroscopy (EIS) can provide crucial information. The EIS spectra of metallic lithium electrodes proved to be more complex than expected, especially when studying thin lithium metal foils. Here, it is identified that charge‐transfer impedance becomes one of the main components of the EIS spectra, the magnitude of which is found to be strongly dependent on the native passivation layer of metallic lithium and on the nature of electrolyte. “Asymmetricity” of the EIS spectra in symmetric cells when separated the working and counter electrode contributions to the total impedance using three‐electrode cells is also identified.
Interspersed Bi Promoting Hot Electron Transfer of Covalent Organic Frameworks Boosts Nitrogen Reduction to ammonia
Authors: Yu Mingfei , Chen Yueling , Gao Ming , Huang Guocheng , Chen Qiaoshan , Bi Jinhong
Published: December 2022

Seeking highly‐efficient, non‐pollutant, and chemically robust photocatalysts for visible‐light‐driven ammonia production still remained challenging, especially in pure water. The key bottle‐necks closely correlate to the nitrogen activation, water oxidization, and hydrogen evolution reaction (HER) processes. In this study, a novel Bi decorated imine‐linked COF‐TaTp (Bi/COF‐TaTp) through N–Bi–O coordination is reasonably designed to achieve a boosting solar‐to‐ammonia conversion of 61 µmol−1 g−1 h−1 in the sacrificial‐free system. On basis of serial characterizations and DFT calculations, the incorporated Bi is conducive to the acceleration of charge carriers transfer and N2 activation through the donation and back‐donation mode. The N2 adsorption energy of 5% Bi/COF‐TaTp is calculated to be −0.19 eV in comparison with −0.09 eV of the pure COF‐TaTp and the electron exchange between N2 and the modified catalyst is much more intensive. Moreover, the accompanied hydrogen production process is effectively inhibited by Bi modification, demonstrated by the higher energy barrier for HER over Bi/COF‐TaTp (2.62 eV) than the pure COF‐TaTp (2.31 eV) when using H binding free energy (ΔGH*) as a descriptor. This work supplies novel insights for the design of photocatalysts for N2 reduction and intensifies the understanding of N2 adsorption and activation over covalent organic frameworks‐based materials.
Pregnancy management and outcome after uterus transplantation
Authors: Mendilcioglu I. , Dogan N. U. , Ozkan O. , Bahceci M. , Boynukalin K. , Dogan S. , Ozkan O.
Published: December 2022

Uterus transplantation is a novel approach in women whose uterus is absent or severely abnormal. However, it is still an experimental procedure that poses risks to both mother and baby. To date, 32 live births after uterus transplantation have been reported in peer‐reviewed journals, with several maternal, fetal and neonatal complications. The most common complications were preterm delivery, hypertensive disorders and placenta previa. Four patients experienced episodes of transplant rejection during pregnancy. The appropriate management of complicated and non‐complicated pregnancies following uterus transplantation is still unresolved. In this review, obstetric outcomes after uterus transplantation and optimal management during pregnancy are discussed in light of the available data. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.
Resilienz von Bildungssystemen: Wie Digitalisierung zur Sicherung des Bildungserfolgs beitragen kann
Authors: Wilhelm-Weidner Arno , Rotter Uwe
Published: December 2022

In der nun schon mehr als zwei Jahre andauernden Corona-Krise lässt sich sozusagen unter dem Mikroskop beobachten, wie die mit den Auswirkungen der Pandemie einhergehenden extremen Stressbelastungen auf die Bildungssysteme in Deutschland einwirken, welche Schwachstellen sich zeigen und welche Maßnahmen nötig sind, um sie resilienter gegen Störungen zu machen. Welche Lehren halten die Pandemie-Erfahrungen bereit und wie können digitale Medien und Techniken dazu beitragen, unser Bildungssystem insgesamt und uns als Lernende individuell krisenfester zu machen?
Resilienz der Biosphäre
Authors: Frey Felix P. , Krahl Perez Cristina , Schliep Rainer
Published: December 2022

Der Mensch verändert seine Umwelt in nie dagewesenem Ausmaß. Die ökologischen Belas-tungsgrenzen der Erde im Bereich der biologischen Vielfalt sind bereits weit überschritten, wodurch die Resilienz der gesamten Biosphäre bedroht ist – und damit auch die Lebensgrundla-gen der Menschheit auf der Erde. Für unsere Gesundheit und unser Überleben auf der Erde brauchen wir Menschen funktionsfähige, vielfältige Ökosysteme. Welchen konkreten Gefahren ist die Biosphäre ausgesetzt? Und welche Möglichkeiten bestehen, vor dem Hintergrund der ak-tuellen Biodiversitätskrise, die Resilienz unserer Biosphäre zu stärken?
Kommunale Resilienz als Innovationsmotor und Garant künftiger Daseinsvorsorge
Authors: Tillack Désriée , Hornbostel Lorenz
Published: December 2022

Digitalisierung, Klimaschutz und Pandemiebekämpfung: Große Herausforderungen und enzgrenzte Krisen rufen immer häufiger nach großen Lösungen. Ein erheblicher Anteil der Umsetzung von Maßnahmen dieser großen Lösungen findet jedoch vor Ort in den mehr als 10.000 Kommunen in Deutschland statt. Vor dem Hintergrund der aktuellen Herausforderungen wird in dem Beitrag aufgezeigt, was resiliente Kommunen auszeichnet, wie sich ihre Resilienz messen lässt – und welche Rolle Resilienz als innovatives Momentum für die kommunale Daseinsvorsorge spielt.
Regional verortet. Gemeinsam stark und resilient – Netzwerke als Impulsgeber
Authors: Buhl Claudia Martina , Ritter Claudia
Published: December 2022

Aufgrund von regionalen Entwicklungs- und Wandlungsprozessen und immer häufiger auf-tretender Krisenphänomene gewinnt der Resilienz-Ansatz in der Regionalentwicklung zu-nehmend an Bedeutung. Netzwerke sind wegen ihrer regionalen Verbundenheit, gefestigten Kooperationskultur, hohen Innovationsfähigkeit und komplementären Kompetenzen der Netzwerkakteure in der Lage auf externe Schocks schnell und koordiniert zu reagieren. Damit bilden sie eine ideale Basis, die Vulnerabilität in ihrer Region zu verringern, deren Regenerationsfähigkeit zu stärken und Impulse auch für andere Regionen zu setzen.
Resiliente und agile Mobilitätssysteme der Zukunft
Authors: Wilsch Benjamin , Martens Martin
Published: December 2022

Mobilität ist Grundvoraussetzung für die Teilhabe am gesellschaftlichen Leben. Was es bedeutet, wenn persönliche Bewegungsfreiheit eingeschränkt oder Mobilität gar unmöglich ist, zeigte sich überdeutlich während der COVID-19-Pandemie. Für die Aufrechterhaltung systemrelevanter Dienste ist somit ein robustes Verkehrssystem mit vielfältigen Mobilitätsangeboten vor allem in urbanen Räumen eine Grundvoraussetzung. Die an Nachhaltigkeit orientierte Mobilitätswende ist mit einer Abkehr vom motorisierten Individualverkehr verbunden und erfordert die Umsetzung neuer Konzepte und Lösungen – wie gestaltet sich der Weg in eine resiliente Mobilitätszukunft?
OLSA-Pegelsteuerung bei monauraler Sprachaudiometrie im Störschall zur Evaluation des CI-Versorgungsergebnisses
Authors: Dziemba Oliver C. , Oberhoffner Tobias , Müller Alexander
Published: December 2022

Hintergrund: Sprachaudiometrische Messungen unter Störschalleinflüssen sind grundlegender Bestandteil bei der Evaluation des Versorgungsergebnisses apparativer Hörversorgungen. Für die adaptive sprachaudiometrische Messung im Störschall bei Cochlea-Implantat(CI)-Trägern:innen existieren bisher noch keine Empfehlungen zur Wahl der Pegelsteuerungsmethode, d. h. entweder die adaptive Pegeländerung des Sprachsignals (S) bei konstantem Störgeräusch (N) oder die adaptive Pegeländerung von N bei konstantem S.

Fragestellung: Hat die verwendete Pegelsteuerung beim Oldenburger Satztest (OLSA) einen Einfluss auf die Ergebnisse der monaural gemessenen Sprachverständlichkeitsschwelle (SVS) im Störschall?

Material und Methoden: Insgesamt wurden von 50 CI-Trägern:innen die im Rahmen der klinischen Routine erzeugten OLSA-Messreihen im Störgeräusch mit unterschiedlicher Pegelsteuerung sowie sprachaudiometrischen Messungen in Ruhe mittels Freiburger Sprachtest ausgewertet und verglichen.

Ergebnisse: In Abhängigkeit von der Pegelsteuerung im OLSA zeigen sich keine signifikanten Unterschiede zwischen den ermittelten Sprachverständlichkeitsschwellen, die kleiner als 5 $$\text{dB}_{\text{S/N}}$$

dB
S/N

sind. Unter 55 % Einsilberverständlichkeit im FBE wird die SVS im OLSA größer als 5 $$\text{dB}_{\text{S/N}}$$

dB
S/N

.

Schlussfolgerungen: Damit bei den Messungen mit positivem S/N der Summenpegel möglichst konstant gehalten wird bzw. nur wenig ansteigt, empfiehlt sich aus klinisch audiologischer und methodischer Sicht die Durchführung der adaptiven monauralen Sprachverständlichkeitsmessung mit konstantem Sprachsignal bei 65 $$\text{dB}_{\text{SPL}}$$

dB
SPL

. Zudem ist die Prüfung der monauralen Sprachverständlichkeit im Störschall erst ab einer Einsilberverständlichkeit von mindestens 55  % (65 $$\text{dB}_{\text{SPL}}$$

dB
SPL

) sinnvoll.
Drohender Kontrollverlust: Überlegungen zu autoritären Anpassungsprozessen im gesellschaftlichen, klinischen und institutionellen Kontext
Authors: Schipflinger Sascha
Published: December 2022

Beginnend mit den 1980er-Jahren hat sich eine neoliberale Marktideologie in globalem Maßstab zunehmend als Referenz für das politische Handeln durchgesetzt. Die soziologischen Untersuchungen von Wilhelm Heitmeyer und Andreas Reckwitz verweisen auf Erosionsprozesse der Mittelschicht, gekennzeichnet durch Kontrollverlust über die Sicherung des eigenen sozioökonomischen Status. Eine damit korrelierende Zuwendung zu autoritären Einstellungen, insbesondere in Gestalt einer unterwürfigen Haltung, wirkt bis tief in die Mitte der Gesellschaft – und damit der Lebenswelt der meisten Psychotherapeut_innen und Patient_innen. Diese strukturell verursachten Problemlagen sensibilisieren für die Frage nach autoritären impliziten Anpassungsprozessen im Feld des Psychotherapeutischen. Wie diese bewusst werden können, wird anhand zweier Ansätze dargestellt: für den klinischen Bereich mit Bernard Brandchafts Abwehrkonzeption als pathologische Anpassungen. Anhand der kritischen Auseinandersetzung mit dem Begriff negative therapeutische Reaktion wird dargestellt, wie ein Verständnis des therapeutischen Prozesses als wechselseitig verfasstes Geschehen für pathologische Anpassungsprozesse sensibilisieren kann. Für den institutionellen Bereich wird Ludwik Flecks Analyse der Tätigkeit wissensorientierter (Ausbildungs‑)Institutionen herangezogen. Seine Verschränkung des Erwerbs und Nachweises fachlicher Kompetenz mit Anpassungen an das, vom Forscherkollektiv geteilte und prämierte Gestalt-Sehen, eröffnet einen alternierenden Blick auf Sozialisationsvorgänge während der Ausbildung. Mithilfe seiner zentralen Begriffe Denkstil und Denkkollektiv wird als (ein) Faktor für Anpassungsprozesse der Zusammenhang zwischen der Offenheit des institutionellen Diskurses und dem Status der Zugehörigkeit ausgewiesen. Was ein institutionelles und klinisches Verständnis als offen auszeichnet, wird abschließend mit Thomas Bauers Begriff der Ambiguitätstoleranz beleuchtet. Damit wird die Bejahung eines Spannungsverhältnisses, das sich aus der Gleichzeitigkeit normsetzender Ansprüche ergibt, bezeichnet. Gezeigt wird, dass einer ambiguitätstoleranten Haltung eine bedeutsame Funktion als Antidot für negative Anpassungsprozesse im gesellschaftlichen, klinischen und institutionellen Kontext zukäme.
The hidden cost of road maintenance due to the increased weight of battery and hydrogen trucks and buses—a perspective
Authors: Low John M. , Haszeldine R. Stuart , Harrison Gareth P.
Published: December 2022

Decarbonisation of transport emissions is essential to meet climate targets. For road transport, currently available technologies are battery electric vehicles and hydrogen fuel cell electric vehicles. Battery vehicles are more established than hydrogen; both could deliver the emissions reduction required. However, battery vehicles are considerably heavier than equivalent hydrogen vehicles, which are in turn slightly heavier than internal combustion engine (ICE) vehicles; a heavier vehicle will have a bigger impact on road wear and associated costs. Here we carry out a desk-based analysis, developed in 2021–2022, examining the impact and cost of the increased weight of zero emissions vehicles on road wear in an entire national vehicle fleet. The novelty is in the first quantified application of the long-understood relationship between axle load and road wear to the problem of the additional weight of zero emissions vehicles. This leads to an approximate quantification of additional costs of road maintenance as the vehicle fleet transitions to zero emissions vehicles. We examine these in four scenarios: all battery vehicles; all hydrogen vehicles; a combination; current ICE vehicles for comparison. We find 20–40% additional road wear associated with battery vehicles compared to ICE vehicles; hydrogen leads to a 6% increase. This is overwhelmingly caused by large vehicles – buses, heavy goods vehicles. Smaller vehicles make a negligible contribution. Governmental bodies liable for road maintenance may wish to set weight limits on roads, require additional axles on heavier vehicles, or construct new roads to a higher standard, to decrease road wear.

Graphical abstract
Electrophysiological and Psychophysical Measures of Temporal Pitch Sensitivity in Normal-hearing Listeners
Authors: Guérit François , Harland Andrew J. , Richardson Matthew L. , Gransier Robin , Middlebrooks John C. , Wouters Jan , Carlyon Robert P.
Published: December 2022

To obtain combined behavioural and electrophysiological measures of pitch perception, we presented harmonic complexes, bandpass filtered to contain only high-numbered harmonics, to normal-hearing listeners. These stimuli resemble bandlimited pulse trains and convey pitch using a purely temporal code. A core set of conditions consisted of six stimuli with baseline pulse rates of 94, 188 and 280 pps, filtered into a HIGH (3365–4755 Hz) or VHIGH (7800–10,800 Hz) region, alternating with a 36% higher pulse rate. Brainstem and cortical processing were measured using the frequency following response (FFR) and auditory change complex (ACC), respectively. Behavioural rate change difference limens (DLs) were measured by requiring participants to discriminate between a stimulus that changed rate twice (up-down or down-up) during its 750-ms presentation from a constant-rate pulse train. FFRs revealed robust brainstem phase locking whose amplitude decreased with increasing rate. Moderate-sized but reliable ACCs were obtained in response to changes in purely temporal pitch and, like the psychophysical DLs, did not depend consistently on the direction of rate change or on the pulse rate for baseline rates between 94 and 280 pps. ACCs were larger and DLs lower for stimuli in the HIGH than in the VHGH region. We argue that the ACC may be a useful surrogate for behavioural measures of rate discrimination, both for normal-hearing listeners and for cochlear-implant users. We also showed that rate DLs increased markedly when the baseline rate was reduced to 48 pps, and compared the behavioural and electrophysiological findings to recent cat data obtained with similar stimuli and methods.
Adaptive Kalman filter based on integer ambiguity validation in moving base RTK
Authors: Wang Zhipeng , Hou Xiaopeng , Dan Zhiqiang , Fang Kun
Published: December 2022

In high-precision dynamic positioning, it is necessary to ensure the positioning accuracy and reliability of the navigation system, especially for safety–critical applications, such as intelligent vehicle navigation. In the face of a complex observation environment, when the global navigation satellite system (GNSS) uses carrier phase observations for high-precision relative positioning, ambiguity resolution will be affected, and it is difficult to estimate all ambiguities. In addition, when the GNSS signal quality and measurement noise level are difficult to predict in an environment with many occlusions, the received satellite observations are prone to very large errors, resulting in apparent deviations in the positioning solution. However, traditional positioning algorithms assume that the measurement noise is constant, which is unrealistic. This will cause incorrect ambiguity resolution, lead to meter-level positioning errors, reduce the reliability of the system, and increase the integrity risk of the system. We proposed an innovative adaptive Kalman filter based on integer ambiguity validation (IAVAKF) to improve the efficiency of ambiguity resolution (AR) and positioning accuracy. The partial ambiguity resolution (PAR) method is applied to solve the integer ambiguities. Then, the accuracy of the fixed ambiguity is verified by the ambiguity success rate. Taking the ambiguity success rate as a dynamic adjustment factor, the measurement noise matrix and variance–covariance matrix of the state estimation is adaptively adjusted at each time interval in the Kalman filter to provide a smoothing effect for filtering. The optimal Kalman filter gain matrix is obtained to improve positioning accuracy and reliability. As a result, the static and dynamic vehicle experiments show that the positioning accuracy of the proposed IAVAKF is improved by 26% compared with the KF. Through the IAVAKF, a more realistic PL can be obtained and applied to evaluate the integrity of the navigation system in the position domain. It can reduce the false alarm rate by 2.45% and 1.85% in the horizontal and vertical directions, respectively.
Determining sex in golden eagle (Aquila chrysaetos) nestlings
Authors: Peniche G. , Shaw D. J. , Dures S. G. , Ciavaglia S. , Thompson D. B. A. , Anderson N. E. , Meredith A. L.
Published: December 2022

Incorporating sex ratios of nestlings into population viability studies increases knowledge of overall health of endangered populations. Currently, a reliable non-invasive method to identify the sex of golden eagle nestlings is not available; however, claims are commonly made based on morphology. Ten biometric measurements from 43 Scottish golden eagles aged 2–7.5 weeks were assessed to see if sex could actually be determined using this non-invasive methodology. Sex was confirmed via molecular analysis of blood samples. Discrete and principal component analyses of the different biometrics could not correctly determine individual nestling sex. Therefore, despite being more invasive, molecular sexing remains the recommended tool of choice for accurate sex identification of Scottish golden eagle nestlings younger than 7.5 weeks of age. This has important implications for golden eagle field studies where empirical morphological measurements are frequently and typically taken, but we have shown are not reliable in determining the sex of such young nestlings.
Same, but Different? Digital Transformation in Swiss Vocational Schools from the Perspectives of School Management and Teachers
Authors: Rauseo Martina , Harder Andreas , Glassey-Previdoli Deborah , Cattaneo Alberto , Schumann Stephan , Imboden Serge
Published: December 2022

The COVID-19 pandemic has further highlighted the importance of the digital transformation of educational organizations. The effects of this transformation process are not limited to the classroom level but extend into various areas of the school, such as Equipment and Technology, Strategy and Leadership, Organization, Employees, and Culture. Against this background, we assessed the status quo of the digital transformation in Swiss vocational schools from the perspective of both school management members and teachers. For this endeavor, two surveys were conducted: the first one in the period from November 2019 to January 2020 (school management members) and the second one between June and September 2020 (teachers). In total, 202 school management members and 1,739 teachers from 62 schools participated in the study. The results of the analyses indicate that the digitization-related dimensions of Strategy and Leadership, as well as Pedagogical IT Support, were perceived better by school management members, whereas teachers considered the areas of Digital Competencies, Attitudes, and Culture to be more advanced. Furthermore, linear regression models show that the dimensions considered important when assessing the status quo of digital transformation differ between the groups. The results emphasize the importance of communication between and the inclusion of all school stakeholders for the successful management of the digital transformation.