bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association of immunological parameters with aortic dilatation in giant cell arteritis: a cross-sectional study
Authors: Jud Philipp , Verheyen Nicolas , Stradner Martin H. , Dejaco Christian , Szolar Dieter , Thonhofer René , Schweiger Leyla , Brodmann Marianne , Hafner Franz 
Published: August 2022

AbstractAortic dilatation (AD) occurs in up to 30% of patients with giant cell arteritis (GCA). Reliable biomarkers for AD development, however, are still absent. The aim of this exploratory study was to evaluate whether immunological parameters are associated with the occurrence of AD in GCA. Cross-sectional study on 20 GCA patients with AD, 20 GCA patients without AD, and 20 non-GCA controls without AD measuring leukocytes, neutrophils, lymphocytes, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), serum amyloid A (SAA), interferon (IFN)-α, IFN-γ, IFN-γ-induced protein 10 (IP-10), interleukin (IL) 5, IL-8, IL-10, IL-17A, IL-18, IL-1 receptor antagonist, tumor necrosis factor (TNF)-α, platelet-derived growth factor (PDGF), L-selectin, P-selectin, and soluble intercellular adhesion molecule 1 (sICAM-1). AD was measured by aortic contrast-enhanced computed tomography and defined by enlargement of the aorta above population-based aortic diameters adjusted by age, gender, and body surface area. No significant differences were observed between GCA patients with AD and GCA patients without AD concerning levels of leukocytes, neutrophils, lymphocytes, CRP, ESR, SAA, IL-8, IL-18, PDGF, IP-10, selectins, and sICAM-1. Values of IFN-α, IFN-γ, IL-5, IL-10, IL-17A, IL-1 receptor antagonist, and TNF-α were all below the detection limits in more than 70% of subjects. Lymphocytes and CRP revealed positive correlations with the diameter of the thoracic descending aorta. Immunological parameters were not useful to conclude on the presence of AD in GCA. Further studies are required to test if CRP and lymphocytes may be useful to predict future development of AD in GCA.
Stability Against the Odds: The Case of Chromonic Liquid Crystals
Authors: Paparini Silvia , Virga Epifanio G. 
Published: August 2022

AbstractThe ground state of chromonic liquid crystals, as revealed by a number of recent experiments, is quite different from that of ordinary nematic liquid crystals: it istwistedinstead of uniform. The common explanation provided for this state within the classical elastic theory of Frank demands that one Ericksen’s inequality is violated. Since in general such a violation makes Frank’s elastic free-energy functional unbounded below, the question arises as to whether the twisted ground state can be locally stable. We answer this question in theaffirmative. In reaching this conclusion, a central role is played by the specific boundary conditions imposed in the experiments on the boundary of rigid containers and by a general formula that we derive here for the second variation in Frank’s elastic free energy.
Olfactory dysfunction is common in classical infratentorial superficial siderosis of the central nervous system
Authors: Kharytaniuk Natallia , Lim E. A. , Chan E. , Pavlou M. , Werring D. J. , Bamiou D. E. 
Published: August 2022

Abstract
Background
Established features of classical infratentorial superficial siderosis (iSS) include hearing loss, impaired balance, myelopathy and, less commonly, cognitive compromise. Olfactory function may be affected but dedicated studies are lacking. This study aimed to assess the prevalence of olfactory dysfunction in iSS and correlate it with auditory and cognitive functions.

Methods
Ten participants with iSS completed the University of Pennsylvania Smell Identification Test (UPSIT). The scores were compared with population norms; regression analysis was performed to evaluate associations between the scores and hearing thresholds (3-frequency average, 3FA) or the number of cognitive domains impaired. Imaging was reviewed for haemosiderin distribution and to exclude other causes of olfactory and hearing dysfunction.

Results
Eight of ten participants were male; the mean (standard deviation, SD) age was 52.5 (14.5) years. Olfactory hypofunction was identified in all participants and in six (60%) was moderate or completely absent. The mean UPSIT score of 25.5 (7.8) was significantly worse than population norms (difference in means − 10.0; 95% CI − 15.6 to − 4.4). Linear regression identified an association between UPSIT and hearing thresholds (R = 0.75; p = 0.013). The score decreases by 0.157 units (95% CI − 0.31 to − 0.002; p = 0.048) per unit increase in 3FA, after adjusting for hearing loss risk factors. There was no statistically significant association between UPSIT and cognitive function (R = 0.383; p = 0.397).

Conclusion
We report a high prevalence of olfactory dysfunction in iSS, the severity of which correlated with hearing loss. Olfaction appears to be a core feature of the iSS clinical syndrome that should be assessed routinely.
Cancer patients’ experiences and preferences when receiving bad news: a qualitative study
Authors: Krieger Theresia , Salm Sandra , Dresen Antje , Cecon Natalia 
Published: August 2022

Abstract
Purpose
Receiving a cancer diagnosis significantly impacts patients’ lives, and how the bad news is delivered influences patients’ trajectory, psychosocial adjustment and openness to psycho-oncological support. We explored how patients’ experiences, reactions and preferences were when receiving the news and which optimization recommendations can be made.

Methods
We conducted an exploratory qualitative study with patients who enrolled in the new integrated cross-sectoral psycho-oncological care programme ‘isPO’, being enrolled 12 months post-diagnosis. Data on the main issue (i.e. perception of the moment when the diagnosis is received) were collected via telephone interviews that were fully audiotaped and transcribed. Two independent coders conducted inductive content analyses using MAXQDA.

Results
Out of 38 approached patients, 23 cancer patients with 13 different tumour entities participated. They had a mean age of 54.2 (SD 16.2); n = 17 (74%) were female. Three major themes with 14 corresponding subthemes emerged: (1) patients’ experiences with the bad news delivery, including setting, mode, preparation and perceived needs; (2) patients’ reactions to the bad news, such as shock, fear and helplessness, disbelief and denial, anger and feeling of injustice, thankfulness and depression; and (3) patients’ receiving preferences, including psycho-oncological support, addressing informational needs, needs-driven comprehensive support and a competent multidisciplinary support team.

Conclusions
The quality of bad news delivery and addressing patients’ needs should be strongly considered by physicians. We recommend integrating patients’ perspective on the quality management processes of breaking bad news. For providing needs-centred high-quality care, applying existing guidelines and acquiring patient-centred communication skills are central.
Non-Preemptive Tree Packing
Authors: Lendl Stefan , Woeginger Gerhard , Wulf Lasse 
Published: August 2022

AbstractAn instance of the non-preemptive tree packing problem consists of an undirected graph $$G=(V,E)$$

G
=
(
V
,
E
)

together with a weight w(e) for every edge $$e\in E$$

e
∈
E

. The goal is to activate every edge e for some time interval of length w(e), such that the activated edges keep G connected for the longest possible overall time. We derive a variety of results on this problem. The problem is strongly NP-hard even on graphs of treewidth 2, and it does not allow a polynomial time approximation scheme (unless P=NP). Furthermore, we discuss the performance of a simple greedy algorithm, and we construct and analyze a number of parameterized and exact algorithms.
The sentiment of a virtual rock concert
Authors: Slater Mel , Cabriera Carlos , Senel Gizem , Banakou Domna , Beacco Alejandro , Oliva Ramon , Gallego Jaime 
Published: August 2022

AbstractWe created a virtual reality version of a 1983 performance by Dire Straits, this being a highly complex scenario consisting of both the virtual band performance and the appearance and behaviour of the virtual audience surrounding the participants. Our goal was to understand the responses of participants, and to learn how this type of scenario might be improved for later reconstructions of other concerts. To understand the responses of participants we carried out two studies which used sentiment analysis of texts written by the participants. Study 1 (n = 25) (Beacco et al. in IEEE Virtual Reality: 538–545, 2021) had the unexpected finding that negative sentiment was caused by the virtual audience, where e.g. some participants were fearful of being harassed by audience members. In Study 2 (n = 26) notwithstanding some changes, the audience again led to negative sentiment—e.g. a feeling of being stared at. For Study 2 we compared sentiment with questionnaire scores, finding that the illusion of being at the concert was associated with positive sentiment for males but negative for females. Overall, we found sentiment was dominated by responses to the audience rather than the band. Participants had been placed in an unusual situation, being alone at a concert, surrounded by strangers, who seemed to pose a social threat for some of them. We relate our findings to the concept of Plausibility, the illusion that events and situations in the VR are really happening. The results indicate high Plausibility, since the negative sentiment, for example in response to being started at, only makes sense if the events are experienced as actually happening. We conclude with the need for co-design of VR scenarios, and the use of sentiment analysis in this process, rather than sole reliance on concepts proposed by researchers, typically expressed through questionnaires, which may not reflect the experiences of participants.
Myocardial scar detection in free-breathing Dixon-based fat- and water-separated 3D inversion recovery late-gadolinium enhancement whole heart MRI
Authors: Peters Alan A. , Wagner Benedikt , Spano Giancarlo , Haupt Fabian , Ebner Lukas , Kunze Karl-Philipp , Schmidt Michaela , Neji Radhouene , Botnar René , Prieto Claudia , Jung Bernd , Christe Andreas , Gräni Christoph , Huber Adrian T. 
Published: August 2022

AbstractThe aim of this study was to investigate the diagnostic accuracy and reader confidence for late-gadolinium enhancement (LGE) detection of a novel free-breathing, image-based navigated 3D whole-heart LGE sequence with fat–water separation, compared to a free-breathing motion-corrected 2D LGE sequence in patients with ischemic and non-ischemic cardiomyopathy. Cardiac MRI patients including the respective sequences were retrospectively included. Two independent, blinded readers rated image quality, depiction of segmental LGE and documented acquisition time, SNR, CNR and amount of LGE. Results were compared using the Friedman or the Kruskal–Wallis test. For LGE rating, a jackknife free-response receiver operating characteristic analysis was performed with a figure of merit (FOM) calculation. Forty-two patients were included, thirty-two were examined with a 1.5 T-scanner and ten patients with a 3 T-scanner. The mean acquisition time of the 2D sequence was significantly shorter compared to the 3D sequence (07:12 min vs. 09:24 min; p < 0.001). The 3D scan time was significantly shorter when performed at 3 T compared to 1.5 T (07:47 min vs. 09:50 min; p < 0.001). There were no differences regarding SNR, CNR or amount of LGE. 3D imaging had a significantly higher FOM (0.89 vs. 0.78; p < 0.001). Overall image quality ratings were similar, but 3D sequence ratings were higher for fine anatomical structures. Free-breathing motion-corrected 3D LGE with high isotropic resolution results in enhanced LGE-detection with higher confidence and better delineation of fine structures. The acquisition time for 3D imaging was longer, but may be reduced by performing on a 3 T-scanner.
Impact of residual extractives on the thermal stability of softwood Kraft pulp
Authors: Jusner Paul , Barbini Stefano , Schiehser Sonja , Bacher Markus , Schwaiger Elisabeth , Potthast Antje , Rosenau Thomas 
Published: August 2022

AbstractWood extractives are known to cause problems during the production of pulp and paper and to impact their mechanical properties. In the present work, we systematically explored whether minute residual amounts of extractives that reprecipitate on the fiber surface in the final stages of the pulping process would lower the thermal resilience of softwood Kraft pulp. Pulp samples subjected to different extraction methods were characterized by means of thermogravimetric analysis. The compound classes constituting the respective extracts were identified and quantified via gas chromatography-mass spectrometry/flame ionization detector (GC-MS/FID) and the influence of the individual compound classes on the thermal stability of the samples was investigated separately. Soxhlet extraction with an ethanol/toluene solvent system clearly led to increased thermal stability. Besides fatty acids and resin acids also sterols and sterol esters that do not carry carboxylic acid functionalities contributed to the deterioration of the thermal pulp properties. Lateral order indices derived from Fourier transformed infrared spectra and crystallinity indices derived from solid-state 13C nuclear magnetic resonance spectra indicate that upon thermal degradation, the presence of even minute amounts of extractives leads to an increased degree of supramolecular disorder. Moreover, the characterization of the samples’ carbohydrate composition by means of acidic hydrolysis showed a tendency towards facilitated pyrolysis of the hemicelluloses if extractives were present in the pulp.
A pre-trained convolutional neural network with optimized capsule networks for chest X-rays COVID-19 diagnosis
Authors: AbouEl-Magd Lobna M. , Darwish Ashraf , Snasel Vaclav , Hassanien Aboul Ella 
Published: August 2022

AbstractCoronavirus disease (COVID-19) is rapidly spreading worldwide. Recent studies show that radiological images contain accurate data for detecting the coronavirus. This paper proposes a pre-trained convolutional neural network (VGG16) with Capsule Neural Networks (CapsNet) to detect COVID-19 with unbalanced data sets. The CapsNet is proposed due to its ability to define features such as perspective, orientation, and size. Synthetic Minority Over-sampling Technique (SMOTE) was employed to ensure that new samples were generated close to the sample center, avoiding the production of outliers or changes in data distribution. As the results may change by changing capsule network parameters (Capsule dimensionality and routing number), the Gaussian optimization method has been used to optimize these parameters. Four experiments have been done, (1) CapsNet with the unbalanced data sets, (2) CapsNet with balanced data sets based on class weight, (3) CapsNet with balanced data sets based on SMOTE, and (4) CapsNet hyperparameters optimization with balanced data sets based on SMOTE. The performance has improved and achieved an accuracy rate of 96.58% and an F1- score of 97.08%, a competitive optimized model compared to other related models.
Assessing covariation as a form of conceptual understanding through comparative judgement
Authors: Bagossi Sara , Ferretti Federica , Arzarello Ferdinando 
Published: August 2022

AbstractThis paper focuses on the importance of covariational reasoning within the processes of mathematics teaching and learning. Despite the internationally recognized relevance of covariation, research shows that only a small percentage of students and teachers is able to adopt covariational reasoning and the majority of mathematics curricula do not contain explicit references to covariational skills. In particular, when covariational reasoning manifests as conceptual knowledge, it becomes challenging to assess, and the need for innovative methods of assessment emerges; there is a need for suitable assessment to highlight the characteristics of covariation and capture the various features that characterize conceptual understanding. Comparative judgement (CJ) is an innovative assessment method based on collective expert judgements of students’ work rather than requiring scoring rubrics. Due to its holistic approach, CJ is particularly suitable for assessing complex mathematical competencies, and, as we shall see in this study, it proved to be appropriate for the covariation’s assessment. In details, our study aims to investigate the perception and relevance attributed by mathematics teachers to covariation as a theoretical construct and the way CJ can help in the assessment of covariational reasoning skills underlying a less structured modelling task.
A Note on Penrose’s Spin-Geometry Theorem and the Geometry of ‘Empirical Quantum Angles’
Authors: Szabados László B. 
Published: August 2022

AbstractIn the traditional formalism of quantum mechanics, a simple direct proof of (a version of) the Spin Geometry Theorem of Penrose is given; and the structure of a model of the ‘space of the quantum directions’, defined in terms of elementary SU(2)-invariant observables of the quantum mechanical systems, is sketched.
AI infers DoS mitigation rules
Authors: Zadnik Martin , Carasec Elena 
Published: August 2022

AbstractDDoS attacks still represent a severe threat to network services. While there are more or less workable solutions to defend against these attacks, there is a significant space for further research regarding automation of reactions. In this article, we focus on one piece of the whole puzzle. We strive to automatically infer filtering rules which are specific to the current DoS attack to decrease the time to mitigation. We employ a machine learning technique to create a model of the traffic mix based on observing network traffic during the attack and normal period. The model is subsequently converted into the filtering rules. We evaluate our approach on several datasets. We experiment with various setups of hyperparameters as well as the various intensity of the attack traffic. The results of our experiments show that the proposed approach is feasible in terms of the capability of inferring successful filtering rules as well as inferring them in a reasonable time.
Synchronization for Networks of Globally Coupled Maps in the Thermodynamic Limit
Authors: Sélley Fanni M. , Tanzi Matteo 
Published: August 2022

AbstractWe study a network of finitely many interacting clusters where each cluster is a collection of globally coupled circle maps in the thermodynamic (or mean field) limit. The state of each cluster is described by a probability measure, and its evolution is given by a self-consistent transfer operator. A cluster is synchronized if its state is a Dirac measure. We provide sufficient conditions for all clusters to synchronize and we describe setups where the conditions are met thanks to the uncoupled dynamics and/or the (diffusive) nature of the coupling. We also give sufficient conditions for partially synchronized states to arise—i.e. states where only a subset of the clusters is synchronized—due to the forcing of a group of cluster on the rest of the network. Lastly, we use this framework to show emergence and stability of chimera states for these systems.
Developments of the k0-NAA measurement model implemented in k0-INRIM software
Authors: Di Luzio Marco , Oddone Massimo , D’Agostino Giancarlo 
Published: August 2022

AbstractThe k0-INRIM software is a computer program that was recently developed to automatically evaluate combined uncertainty while performing mass fraction measurements adopting the k0-standardization method of Neutron Activation Analysis. In this paper, significant developments of the adopted measurement model, following a complete revision of the detector characterization procedure, are reported. In particular, the efficiency ratio between monitor and analyte γ-emissions accounts for conversions between counting positions, extended sample geometry and self-absorption. In addition, true-coincidence summing, neutron flux gradient, moisture and blank corrections are included in the model. The developed measurement model is implemented in the latest k0-INRIM release; this greatly improves flexibility of the software in most of the common situations encountered in routine analysis without losing its inherent characteristic focused on uncertainty evaluation through propagation of covariances via sensitivity coefficients. A performance test was carried out by measuring the Au mass fraction of a cylindrical sample prepared from electronic waste material. Results obtained by counting the sample at different positions with respect to the detector end-cap are presented.
Robust DC optimal power flow with modeling of solar power supply uncertainty via R-vine copulas
Authors: Aigner Kevin-Martin , Schaumann Peter , Loeper Freimut von , Martin Alexander , Schmidt Volker , Liers Frauke 
Published: August 2022

AbstractWe present a robust approximation of joint chance constrained DC optimal power flow in combination with a model-based prediction of uncertain power supply via R-vine copulas. It is applied to optimize the discrete curtailment of solar feed-in in an electrical distribution network and guarantees network stability under fluctuating feed-in. This is modeled by a two-stage mixed-integer stochastic optimization problem proposed by Aigner et al. (Eur J Oper Res (2022) https://doi.org/10.1016/j.ejor.2021.10.051). The solution approach is based on the approximation of chance constraints via robust constraints using suitable uncertainty sets. The resulting robust optimization problem has a known equivalent tractable reformulation. To compute uncertainty sets that lead to an inner approximation of the stochastic problem, an R-vine copula model is fitted to the distribution of the multi-dimensional power forecast error, i.e., the difference between the forecasted solar power and the measured feed-in at several network nodes. The uncertainty sets are determined by encompassing a sufficient number of samples drawn from the R-vine copula model. Furthermore, an enhanced algorithm is proposed to fit R-vine copulas which can be used to draw conditional samples for given solar radiation forecasts. The experimental results obtained for real-world weather and network data demonstrate the effectiveness of the combination of stochastic programming and model-based prediction of uncertainty via copulas. We improve the outcomes of previous work by showing that the resulting uncertainty sets are much smaller and lead to less conservative solutions while maintaining the same probabilistic guarantees.