bluuebunny/crossref_metadata_2025_split huggingface dataset:
Band-selective universal 90° and 180° rotation pulses covering the aliphatic carbon chemical shift range for triple resonance experiments on 1.2 GHz spectrometers
Authors: Slad Stella , Bermel Wolfgang , Kümmerle Rainer , Mathieu Daniel , Luy Burkhard 
Published: November 2022

AbstractBiomolecular NMR spectroscopy requires large magnetic field strengths for high spectral resolution. Today’s highest fields comprise proton Larmor frequencies of 1.2 GHz and even larger field strengths are to be expected in the future. In protein triple resonance experiments, various carbon bandwidths need to be excited by selective pulses including the large aliphatic chemical shift range. When the spectrometer field strength is increased, the length of these pulses has to be decreased by the same factor, resulting in higher rf-amplitudes being necessary in order to cover the required frequency region. Currently available band-selective pulses like Q3/Q5 excite a narrow bandwidth compared to the necessary rf-amplitude. Because the maximum rf-power allowed in probeheads is limited, none of the selective universal rotation pulses reported so far is able to cover the full $$^{13}$$

13

C aliphatic region on 1.2 GHz spectrometers. In this work, we present band-selective 90° and 180° universal rotation pulses (SURBOP90 and SURBOP180) that have a higher ratio of selective bandwidth to maximum rf-amplitude than standard pulses. Simulations show that these pulses perform better than standard pulses, e. g. Q3/Q5, especially when rf-inhomogeneity is taken into account. The theoretical and experimental performance is demonstrated in offset profiles and by implementing the SURBOP pulses in an HNCACB experiment at 1.2 GHz.
How Software Agents Can Help to Coordinate Emergency Response Teams: Adaptive Team Performance Comparing Manual and Automated Team Communication
Authors: Müller Rebecca , Graf Benedikt , Ellwart Thomas , Antoni Conny H. 
Published: November 2022

Abstract
In interprofessional emergency response teams, firefighters, police, and paramedics must communicate efficiently (i.e., request the correct expert) to avoid life-threatening consequences. However, this communication is sometimes inefficient, for example, when a wrong expert is requested due to the lack of meta-knowledge. Team research has shown that meta-knowledge of “who knows what” improves team communication, so that members correctly request each other according to their expertise. Advances in technology, such as software agents holding meta-knowledge, can be used to improve team communication. In this paper, we analyze the effects of meta-knowledge on expert seeking, mistakes in requesting experts, and (adaptive) team performance by comparing manual and automated agent-based team communication. Using a control-center simulation, 360 students in 120 three-person teams had the interdependent task of handling emergencies in three phases. We manipulated meta-knowledge in advance, with 61 teams learning and 59 teams not learning other team members’ expertise. Furthermore, in phases 1 and 3, team members had to communicate manually. In phase 2, communication was automated by a software agent taking over expert requesting. In line with our hypotheses, results showed that software agents can compensate the lack of meta-knowledge, so that there were no performance differences between teams with and without meta-knowledge with automated team communication. Our findings provide implications for research and practice that established team constructs should also be considered in human-automation teams.
Religious Experience as a Predictor of the Meaning in Life and Life Satisfaction in the Lives of Polish Women after a Stillbirth
Authors: Głaz Stanisław 
Published: November 2022

AbstractMany researchers have demonstrated the relationship of religiosity with dimensions of mental health such as searching for meaning in life, the presence of meaning in life, and life satisfaction. Hence, this study attempts to link such aspects of religiosity with the experience of the presence and/or absence of God with the search for and presence of meaning in life and satisfaction with life among a group of Polish women who have experienced a stillbirth in the past five years. The study included 64 women who lost a baby through stillbirth after the 22nd week of gestation. All the women were born into Christian families and declared themselves to be Christians and actively practicing their faith. Women’s ages ranged from 29 to 47 years. The research results showed that the experience of God’s presence and absence have a positive and significant relationship with the search for meaning in life and the presence of meaning in life, as well as with the satisfaction with life in the lives of women after stillbirth. The strongest relationship was between the presence of meaning in life and life satisfaction (r = .72; p < .01), God’s presence and life satisfaction (r = .66; p < .01), as well as the presence of meaning in life and the search for meaning in life (r = .57; p < .01). The structural equation model showed that the experience of God’s presence and God’s absence have a significant, direct impact on the search for meaning in life and the presence of meaning in life, and the satisfaction with life. These also have an indirect impact on the satisfaction with life in the lives of women who have lost a child to stillbirth.
The predominant stride-frequency for routine swimming in catsharks (Scyliorhinus canicula) generates high power at high efficiency in the red musculature
Authors: West Timothy G. , Curtin Nancy A. , Woledge Roger C. 
Published: November 2022

AbstractVideos of free swimming of catsharks (Scyliorhinus canicula) were analysed to give values of swimming speed (units: FL (fish lengths) s−1), stride-length (forward movement in the direction of travel per cycle of body undulation (units: FL) and stride-frequency (units: s−1). Most of the swims (139 of 163, 85%) were at speeds less than 0.545 FL s−1 and were categorized as slow. The rest (24/163, 15%) were categorized as fast. Stride-lengths and stride-frequencies could be evaluated for 115 of the slow swims and 16 of the fast swims. We discuss the fast swim results, but there were so few fast swims that no firm conclusions could be made. As swim speed increased during slow swims, there was a strong increase stride-length [slope 0.965, P < 0.0001)] and a small increase in stride-frequency. Most stride-frequencies (70/115, 61%) were in the range 0.68–0.88 s−1. Previous experiments on red muscle isolated of catshark showed that in this range of frequencies of sinusoidal movement, high power was produced at high efficiency (Curtin and Woledge b). Lower frequencies gave less power and at higher frequencies the efficiency of energy conversion was lower. Thus, we conclude that during routine swimming catsharks choose a swimming speed that optimizes red muscle performance in terms of power and efficiency.
Automated habitat monitoring systems linked to adaptive management: a new paradigm for species conservation in an era of rapid environmental change
Authors: Shirk Andrew J. , Jones Gavin M. , Yang Zhiqiang , Davis Raymond J. , Ganey Joseph L. , Gutiérrez R. J. , Healey Sean P. , Hedwall Shaula J. , Hoagland Serra J. , Maes Ron , Malcolm Karl , McKelvey Kevin S. , Vynne Carly , Sanderlin Jamie S. , Schwartz Michael K. , Seamans Mark E. , Wan Ho Yi , Cushman Samuel A. 
Published: November 2022

Abstract
Context
Recent increases in ecological disturbances driven by climate change and our expanding human footprint make it challenging for natural resource managers to keep apprised of current conditions and adjust management plans accordingly. To effectively conserve species in highly dynamic landscapes requires more timely habitat monitoring and a more responsive adaptive management cycle.

Objectives
We introduce a framework to automatically monitor and assess species habitats over a range of spatial and temporal scales. We then apply this framework by developing an automated habitat monitoring system for the Mexican spotted owl (MSO) in Arizona and New Mexico, USA, that will be linked to federal agency adaptive management plans.

Methods
We automated the process of monitoring and assessing trends in MSO habitat on an annual schedule using the Google Earth Engine cloud-based spatial analysis platform and dynamic data repository. We ran this system retrospectively on historical data to monitor MSO habitat from 1986 to 2020.

Results
The automated habitat monitoring system provided a 35-year MSO habitat time series with high accuracy. Widespread habitat gains and losses occurred every year, underscoring the need for continuous monitoring and the benefits of an automated workflow.

Conclusions
Automated habitat monitoring linked to adaptive management holds great promise in helping managers track the impacts of recent disturbances and adjust plans to meet goals even in increasingly dynamic landscapes. In a companion paper, Jones et al. (2023) demonstrate the utility of this approach by analyzing our MSO habitat time series to assess trends, drivers of change, and management implications.
SLISEMAP: supervised dimensionality reduction through local explanations
Authors: Björklund Anton , Mäkelä Jarmo , Puolamäki Kai 
Published: November 2022

AbstractExisting methods for explaining black box learning models often focus on building local explanations of the models’ behaviour for particular data items. It is possible to create global explanations for all data items, but these explanations generally have low fidelity for complex black box models. We propose a new supervised manifold visualisation method, slisemap, that simultaneously finds local explanations for all data items and builds a (typically) two-dimensional global visualisation of the black box model such that data items with similar local explanations are projected nearby. We provide a mathematical derivation of our problem and an open source implementation implemented using the GPU-optimised PyTorch library. We compare slisemap to multiple popular dimensionality reduction methods and find that slisemap is able to utilise labelled data to create embeddings with consistent local white box models. We also compare slisemap to other model-agnostic local explanation methods and show that slisemap provides comparable explanations and that the visualisations can give a broader understanding of black box regression and classification models.
DLC-Coated Thermoplastics: Tribological Analyses Under Dry and Lubricated Sliding Conditions
Authors: Bobzin K. , Kalscheuer C. , Thiex M. , Sperka P. , Hartl M. , Reitschuster S. , Maier E. , Lohner T. , Stahl K. 
Published: November 2022

AbstractThe purpose of this study was to increase the limited wear resistance of polymers in highly stressed tribological contacts. Therefore, diamond-like carbon (DLC) coatings were firstly developed and deposited on polymers. The development of the low temperature coating process was conducted on an industrial scale coating unit. Due to the use of polyether ether ether ketone (PEEK) and polyamide as substrate material, the coatings were tailored in accordance with different mechanical properties of the polymers. Furthermore, analyses regarding morphology, roughness as well as compound adhesion between coatings and polymers were conducted. The tribological analyses were accomplished for reciprocating sliding kinematics on pin-on-plate tribometer under dry conditions as well as boundary lubricated conditions. The results prove the ability of the coatings to undergo high plastic deformations without delamination. In addition, the possible formation of a composite layer of DLC and PEEK in the wear track due to high energy input under dry conditions was shown. Furthermore, the transformations of sp2 chain into ring bindings as well as a change of size and distribution of the sp2 clusters during dry contact conditions were observed.
Application of Tribological Artificial Neural Networks in Machine Elements
Authors: Walker J. , Questa H. , Raman A. , Ahmed M. , Mohammadpour M. , Bewsher S. R. , Offner G. 
Published: November 2022

AbstractTraditionally, analytical equations used in tribo-dynamic modelling, such as those used for predicting central film thickness within elastohydrodynamic lubricated contacts, have led to timely computations, but tend to lack the accuracy of numerical solvers. However, it can be shown that data-driven solutions, such as machine learning, can significantly improve computational efficiency of tribo-dynamic simulations of machine elements without comprising accuracy relative to the numerical solution. During this study, artificial neural networks (ANNs) are trained using data produced via numerical solutions, which are constrained by the regimes of lubrication to ensure the quality of the training data set. Multiple ANNs are then implemented to predict EHL central film thickness, as well as viscous and boundary friction, in multiple commonly used machine elements, such as a rolling element bearing and a spur gear. The viscous and boundary friction ANN prediction are compared directly against ball-on-disc experimental measurements to validate its accuracy.
Circumventing the Non-identity Problem
Authors: Carey Brian 
Published: November 2022

AbstractThis article provides an account of moral obligations that we have towards present generations, which require us to produce outcomes that are similar to those we would be required to produce if we had moral obligations to future generations. Discharging these duties enables us to secure the kinds of goods for future generations that we intuitively think we ought to provide in the absence of an answer to the non-identity problem. In this sense, the non- identity problem is avoided rather than solved. Nevertheless, a significant upshot of this account is that it provides a basis for practical action in the face of theoretical uncertainty.
A virtual surgical prototype system based on gesture recognition for virtual surgical training in maxillofacial surgery
Authors: Zhao Hanjiang , Cheng Mengjia , Huang Jingyang , Li Meng , Cheng Huanchong , Tian Kun , Yu Hongbo 
Published: November 2022

Abstract
Background
Virtual reality (VR) technology is an ideal alternative of operation training and surgical teaching. However, virtual surgery is usually carried out using the mouse or data gloves, which affects the authenticity of virtual operation. A virtual surgery system with gesture recognition and real-time image feedback was explored to realize more authentic immersion.

Method
Gesture recognition technology proposed with an efficient and real-time algorithm and high fidelity was explored. The recognition of hand contour, palm and fingertip was firstly realized by hand data extraction. Then, an Support Vector Machine classifier was utilized to classify and recognize common gestures after extraction of feature recognition. The algorithm of collision detection adopted Axis Aligned Bounding Box binary tree to build hand and scalpel collision models. What’s more, nominal radius theorem (NRT) and separating axis theorem (SAT) were applied for speeding up collision detection. Based on the maxillofacial virtual surgical system we proposed before, the feasibility of integration of the above technologies in this prototype system was evaluated.

Results
Ten kinds of signal static gestures were designed to test gesture recognition algorithms. The accuracy of gestures recognition is more than 80%, some of which were over 90%. The generation speed of collision detection model met the software requirements with the method of NRT and SAT. The response time of gesture] recognition was less than 40 ms, namely the speed of hand gesture recognition system was greater than 25 Hz. On the condition of integration of hand gesture recognition, typical virtual surgical procedures including grabbing a scalpel, puncture site selection, virtual puncture operation and incision were carried out with realization of real-time image feedback.

Conclusion
Based on the previous maxillofacial virtual surgical system that consisted of VR, triangular mesh collision detection and maxillofacial biomechanical model construction, the integration of hand gesture recognition was a feasible method to improve the interactivity and immersion of virtual surgical operation training.
Online-Meetings: Fluch und Segen eines digitalen Kommunikationsformats
Authors: Kunert Sebastian 
Published: November 2022

ZusammenfassungDieser Artikel widmet sich virtuellen Konferenzformaten und deren Eigenheiten. Aus verschiedenen psychologischen Perspektiven wird der Frage nachgegangen, was Online-Meetings von Präsenztreffen unterscheidet, wo die Gründe für die vorzeitige Erschöpfung in solchen digitalen Formaten liegen und welchen Risiken man sich bei ihrem Einsatz bewusst sein muss. Der Beitrag endet mit einem Plädoyer für eine integrative Perspektive von Präsenz, asynchronen und synchronen digitalen Kommunikationsformaten.
The Isothermal Oxidation of a New Polycrystalline Turbine Disk Ni-Based Superalloy at 800 °C and Its Modification with Pre-oxidation
Authors: Wo J. W. X. , Pang H. T. , Wilson A. S. , Hardy M. C. , Stone H. J. 
Published: November 2022

AbstractNi-based superalloys with enhanced oxidation resistance at high temperatures are crucial for next-generation gas turbine engines. A new polycrystalline Ni-based superalloy (C19) that combines improved microstructural stability with environmental resistance has been developed. Its oxidation resistance has been determined through measurements of the specific mass change and morphological evolution of the formed oxides following furnace exposures at 800 °C in air for up to 1000 hours; the results of which were benchmarked against Nimonic 105. C19 showed hybrid Type II/Type III behavior as a marginal Al2O3former and performed similarly to established superalloys at 750 °C. The Wagner model for the transition from internal to external oxide formation predicted that C19 should form a continuous Al2O3scale at higher temperatures. A pre-oxidation treatment at 1100 °C for 1 hour was, therefore, selected and shown to dramatically improve the oxidation resistance during subsequent exposure at 800 °C. Oxide cross-sectional analysis showed that C19 formed a continuous and protective Al2O3scale after the pre-oxidation treatment, whereas Nimonic 105 retained discontinuous Al2O3finger-like intrusions beneath a Cr2O3overscale.
Repression, Retraction? Re-reading!
Authors: Preuß Kai 
Published: November 2022

AbstractSince there have been books, there has been a need to get rid of them. From powerful magical formulae and heretical wisdom to the early drafts of poetry, authorities and writers tried to remove certain texts from circulation, or tried to inhibit or steer their reception. In the first part, this article gives a brief overview of forms of book-disposal, voluntary and involuntary, in antiquity and points to their significance for Augustine of Hippo in particular. In a second section, the article features Augustine’sRevisions(Retractationes), a commentary on his own literary production and an innovative effort to gain control over the reception and interpretation of his own works. In this late retrospection, Augustine employs the persona of a self-critical author—fallible and pressed by the duties of his office but always in pursuit of God’s truth—that allows him to reconfigure his authorial past in relation to himself, his texts, and his audience. The article will trace the implications of Augustine’s self-fashioning for the recurrent problem of controlling the reception and interpretation of written works.
Explaining variation in adolescents’ social media-related distraction: The role of social connectivity and disconnectivity factors
Authors: Siebers Teun , Beyens Ine , Pouwels J. Loes , Valkenburg Patti M. 
Published: November 2022

AbstractSocial media are often believed to distract adolescents’ attention. While existing research has shown that some adolescents experience more social media-related distraction than others, the explanations for these differences remain largely unknown. Based on Self-Determination Theory, this preregistered study investigated two social connectivity factors (fear of missing out [FoMO] and friendship accessibility expectations) and two disconnectivity factors (self-control strategies and parental restrictions) that may explain heterogeneity in social media-related distraction. We used data collected through a measurement burst design, consisting of a three-week experience sampling method study among 300 adolescents (21,970 assessments) and online surveys. Using N = 1 analyses, we found that most adolescents (77%) experienced social media-related distraction. Contrary to expectations, none of the connectivity or disconnectivity factors explained differences in social media-related distraction. The findings indicate that social media are a powerful distractor many adolescents seem to struggle with.
Is trust in artificial intelligence systems related to user personality? Review of empirical evidence and future research directions
Authors: Riedl René 
Published: November 2022

AbstractArtificial intelligence (AI) refers to technologies which support the execution of tasks normally requiring human intelligence (e.g., visual perception, speech recognition, or decision-making). Examples for AI systems are chatbots, robots, or autonomous vehicles, all of which have become an important phenomenon in the economy and society. Determining which AI system to trust and which not to trust is critical, because such systems carry out tasks autonomously and influence human-decision making. This growing importance of trust in AI systems has paralleled another trend: the increasing understanding that user personality is related to trust, thereby affecting the acceptance and adoption of AI systems. We developed a framework of user personality and trust in AI systems which distinguishes universal personality traits (e.g., Big Five), specific personality traits (e.g., propensity to trust), general behavioral tendencies (e.g., trust in a specific AI system), and specific behaviors (e.g., adherence to the recommendation of an AI system in a decision-making context). Based on this framework, we reviewed the scientific literature. We analyzed N = 58 empirical studies published in various scientific disciplines and developed a “big picture” view, revealing significant relationships between personality traits and trust in AI systems. However, our review also shows several unexplored research areas. In particular, it was found that prescriptive knowledge about how to design trustworthy AI systems as a function of user personality lags far behind descriptive knowledge about the use and trust effects of AI systems. Based on these findings, we discuss possible directions for future research, including adaptive systems as focus of future design science research.
Ist das (schon) Hatespeech? – Eine qualitative Untersuchung zum Verständnis von Hatespeech unter pädagogischem Schulpersonal
Authors: Ballaschk Cindy , Schulze-Reichelt Friederike , Wachs Sebastian , Krause Norman , Wettstein Alexander , Kansok-Dusche Julia , Bilz Ludwig , Schubarth Wilfried 
Published: November 2022

ZusammenfassungHatespeech ist ein gesellschaftliches Phänomen, das auch die Lebenswelt Schule betrifft. Was jedoch pädagogisches Schulpersonal unter Hatespeech versteht, ist unklar und daher Thema der vorliegenden Interviewstudie mit Lehrkräften (n = 18) und Sozialpädagog_innen (n = 16). Die Ergebnisse zeigen, dass Hatespeech als Herabsetzung verschiedener strukturell unterdrückter Gruppen verstanden wird (z. B. Transpersonen, Homosexuelle, jüdische Personen). Die Befragten erkennen subtilere Formen von Hatespeech oft nicht als Problem an und verstehen Hatespeech vorranging als Online-Phänomen, obwohl auch Vorfälle in Schulen berichtet werden. Es lässt sich schlussfolgern, dass pädagogisches Schulpersonal für Offline-Hatespeech und subtilere Formen sensibilisiert werden muss, um seine Interventionsbereitschaft zu steigern.