bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multilingual writing development: Relationships between writing proficiencies in German, heritage language and English
Authors: Schnoor Birger , Usanova Irina 
Published: June 2022

AbstractWriting, as a highly complex strategic literacy skill alongside reading, is an essential prerequisite for learning and determines a student’s educational success. In diverse contexts, a student’s linguistic repertoire may involve multiple languages, which may serve as mutual resources in his or her multilingual writing skill development. Drawing on the data from a German panel study, “Multilingual Development: A Longitudinal Perspective”, the current research used the longitudinal writing competence data of 965 German-Russian and German-Turkish secondary students regarding their majority language (German), heritage language (Russian or Turkish), and foreign language (English). We applied longitudinal structural equation modeling to investigate within- and between-language effects in multilingual writing development over three waves of data collection. Accordingly, our study extends previous research on the interrelation of languages in multilingual writing development in two ways. First, we provide a more comprehensive analysis of migrant students’ multilingual writing repertoires by simultaneously evaluating three languages in an integrative model of multilingual writing development. Second, we use longitudinal competence data to decompose covariance between languages to isolate the parts of the variances that truly predict changes within and between languages. This approach empirically tests the resources hypothesis more rigorously than extant evaluations. In summary, our findings indicate that language-specific writing skills may serve as mutual resources for developing multilingual writing proficiency.
High-dimensional regression with potential prior information on variable importance
Authors: Stokell Benjamin G. , Shah Rajen D. 
Published: June 2022

AbstractThere are a variety of settings where vague prior information may be available on the importance of predictors in high-dimensional regression settings. Examples include the ordering on the variables offered by their empirical variances (which is typically discarded through standardisation), the lag of predictors when fitting autoregressive models in time series settings, or the level of missingness of the variables. Whilst such orderings may not match the true importance of variables, we argue that there is little to be lost, and potentially much to be gained, by using them. We propose a simple scheme involving fitting a sequence of models indicated by the ordering. We show that the computational cost for fitting all models when ridge regression is used is no more than for a single fit of ridge regression, and describe a strategy for Lasso regression that makes use of previous fits to greatly speed up fitting the entire sequence of models. We propose to select a final estimator by cross-validation and provide a general result on the quality of the best performing estimator on a test set selected from among a numberMof competing estimators in a high-dimensional linear regression setting. Our result requires no sparsity assumptions and shows that only a$$\log M$$logMprice is incurred compared to the unknown best estimator. We demonstrate the effectiveness of our approach when applied to missing or corrupted data, and in time series settings. An R package is available on github.
Two accounts of assertion
Authors: Smith Martin 
Published: June 2022

AbstractIn this paper I will compare two competing accounts of assertion: the knowledge account and the justified belief account. When it comes to the evidence that is typically used to assess accounts of assertion—including the evidence from lottery propositions, the evidence from Moore’s paradoxical propositions and the evidence from conversational patterns—I will argue that the justified belief account has at least as much explanatory power as its rival. I will argue, finally, that a close look at the ways in which assertions can be challenged and retracted reveals a certain advantage for the justified belief account. The paper will touch upon a number of further topics along the way, including the logical interaction between knowledge and justified belief, the nature of defeat, and the hypothesis that knowledge and justified belief are normatively coincident goals.
Towards a More Robust Evaluation of Climate Model and Hydrological Impact Uncertainties
Authors: Pastén-Zapata E. , Eberhart T. , Jensen K. H. , Refsgaard J. C. , Sonnenborg T. O. 
Published: June 2022

AbstractThe uncertainty of climate model projections is recognized as being large. This represents a challenge for decision makers as the simulation spread of a climate model ensemble can be large, and there might even be disagreement on the direction of the climate change signal among the members of the ensemble. This study quantifies changes in the hydrological projection uncertainty due to different approaches used to select a climate model ensemble. The study assesses 16 Euro-CORDEX Regional Climate Models (RCMs) that drive three different conceptualizations of the MIKE-SHE hydrological model for the Ahlergaarde catchment in western Denmark. The skills of the raw and bias-corrected RCMs to simulate historical precipitation are evaluated using sets of nine, six, and three metrics assessing means and extremes in a series of steps, and results in reduction of projection uncertainties. After each step, the overall lowest-performing model is removed from the ensemble and the standard deviation is estimated, only considering the members of the new ensemble. This is performed for nine steps. The uncertainty of raw RCM outputs is reduced the most for river discharge (5 th , 50 th and 95 th percentiles) when using the set of three metrics, which only assess precipitation means and one ‘moderate’ extreme metrics. In contrast, the uncertainty of bias-corrected RCMs is reduced the most when using all nine metrics, which evaluate means, ‘moderate’ extremes and high extremes. Similar results are obtained for groundwater head (GWH). For the last step of the method, the initial standard deviation of the raw outputs decreases up to 38% for GWH and 37% for river discharge. The corresponding decreases when evaluating the bias-corrected outputs are 63% and 42%. For the bias corrected outputs, the approach proposed here reduces the projected hydrological uncertainty and provides a stronger change signal for most of the months. This
analysis provides an insight on how different approaches used to select a climate
model ensemble affect the uncertainty of the hydrological projections and, in this case,
reduce the uncertainty of the future projections.
PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management
Authors: Paulhe Nils , Canlet Cécile , Damont Annelaure , Peyriga Lindsay , Durand Stéphanie , Deborde Catherine , Alves Sandra , Bernillon Stephane , Berton Thierry , Bir Raphael , Bouville Alyssa , Cahoreau Edern , Centeno Delphine , Costantino Robin , Debrauwer Laurent , Delabrière Alexis , Duperier Christophe , Emery Sylvain , Flandin Amelie , Hohenester Ulli , Jacob Daniel , Joly Charlotte , Jousse Cyril , Lagree Marie , Lamari Nadia , Lefebvre Marie , Lopez-Piffet Claire , Lyan Bernard , Maucourt Mickael , Migne Carole , Olivier Marie-Francoise , Rathahao-Paris Estelle , Petriacq Pierre , Pinelli Julie , Roch Léa , Roger Pierrick , Roques Simon , Tabet Jean-Claude , Tremblay-Franco Marie , Traïkia Mounir , Warnet Anna , Zhendre Vanessa , Rolin Dominique , Jourdan Fabien , Thévenot Etienne , Moing Annick , Jamin Emilien , Fenaille François , Junot Christophe , Pujos-Guillot Estelle , Giacomoni Franck 
Published: June 2022

Abstract
Introduction
Accuracy of feature annotation and metabolite identification in biological samples is a key element in metabolomics research. However, the annotation process is often hampered by the lack of spectral reference data in experimental conditions, as well as logistical difficulties in the spectral data management and exchange of annotations between laboratories.

Objectives
To design an open-source infrastructure allowing hosting both nuclear magnetic resonance (NMR) and mass spectra (MS), with an ergonomic Web interface and Web services to support metabolite annotation and laboratory data management.

Methods
We developed the PeakForest infrastructure, an open-source Java tool with automatic programming interfaces that can be deployed locally to organize spectral data for metabolome annotation in laboratories. Standardized operating procedures and formats were included to ensure data quality and interoperability, in line with international recommendations and FAIR principles.

Results
PeakForest is able to capture and store experimental spectral MS and NMR metadata as well as collect and display signal annotations. This modular system provides a structured database with inbuilt tools to curate information, browse and reuse spectral information in data treatment. PeakForest offers data formalization and centralization at the laboratory level, facilitating shared spectral data across laboratories and integration into public databases.

Conclusion
PeakForest is a comprehensive resource which addresses a technical bottleneck, namely large-scale spectral data annotation and metabolite identification for metabolomics laboratories with multiple instruments. PeakForest databases can be used in conjunction with bespoke data analysis pipelines in the Galaxy environment, offering the opportunity to meet the evolving needs of metabolomics research. Developed and tested by the French metabolomics community, PeakForest is freely-available at https://github.com/peakforest.
Striatal Dopaminergic Depletion Pattern Reflects Pathological Brain Perfusion Changes in Lewy Body Diseases
Authors: Iwabuchi Yu , Shiga Tohru , Kameyama Masashi , Miyazawa Raita , Seki Morinobu , Ito Daisuke , Uchida Hiroyuki , Tabuchi Hajime , Jinzaki Masahiro 
Published: June 2022

Abstract
Purpose
In Lewy body diseases (LBD), various symptoms occur depending on the distribution of Lewy body in the brain, and the findings of brain perfusion and dopamine transporter single-photon emission computed tomography (DAT-SPECT) also change accordingly. We aimed to evaluate the correlation between brain perfusion SPECT and quantitative indices calculated from DAT-SPECT in patients with LBD.

Procedures
We retrospectively enrolled 35 patients with LBD who underwent brain perfusion SPECT with N-isopropyl-p-[123I] iodoamphetamine and DAT-SPECT with 123I-ioflupane. Mini-mental state examination (MMSE) data were also collected from 19 patients. Quantitative indices (specific binding ratio [SBR], putamen-to-caudate ratio [PCR], and caudate-to-putamen ratio [CPR]) were calculated using DAT-SPECT. These data were analysed by the statistical parametric mapping procedure.

Results
In patients with LBD, decreased PCR index correlated with hypoperfusion in the brainstem (medulla oblongata and midbrain) (uncorrected p < 0.001, k > 100), while decreased CPR index correlated with hypoperfusion in the right temporoparietal cortex (family-wise error corrected p < 0.05), right precuneus (uncorrected p < 0.001, k > 100), and bilateral temporal cortex (uncorrected p < 0.001, k > 100). However, there was no significant correlation between decreased SBR index and brain perfusion. Additionally, the MMSE score was correlated with hypoperfusion in the left temporoparietal cortex (uncorrected p < 0.001).

Conclusions
This study suggests that regional changes in striatal 123I-ioflupane accumulation on DAT-SPECT are related to brain perfusion changes in patients with LBD.
Why do firms down-list or exit from securities markets?
Authors: Bessler Wolfgang , Beyenbach Johannes , Rapp Marc Steffen , Vendrasco Marco 
Published: June 2022

AbstractIn 2003, the German Stock Exchange instituted thePrime Standardas the highest regulated stock market segment in Germany. We analyze the firms’ delisting decisions from this market segment between 2003 and 2015, with a focus on different delisting reasons and firm characteristics. We identify 518 firms that listed on thePrime Standardat least once during the sample period of which 243 firms left this market segment. Of these firms, 107 down-listed and transferred to lower market segments and 136 firms exited the public equity market for the following reasons: 61 firms merged, 53 were insolvent, and 22 firms went private. Using cross-sectional and firm-fixed effects logit regressions, we provide new evidence for firms’ market segment and delisting decisions. Consistent with a cost–benefit analysis, we observe that inferior growth opportunities, low stock liquidity, smaller firm size, poor operating performance, higher audit fees, and more agency conflicts increase the probability that firms opt for a less regulated stock market segment or voluntarily go private. This raises the important issue of securities market reforms that best meet firms and investors preferences.
A novel epithelial–mesenchymal transition gene signature for the immune status and prognosis of hepatocellular carcinoma
Authors: Shi Yanlong , Wang Jingyan , Huang Guo , Zhu Jun , Jian Haokun , Xia Guozhi , Wei Qian , Li Yuanhai , Yu Hongzhu 
Published: June 2022

Abstract
Background
This study clarified whether EMT-related genes can predict immunotherapy efficacy and overall survival in patients with HCC.

Methods
The RNA-sequencing profiles and patient information of 370 samples were derived from the Cancer Genome Atlas (TCGA) dataset, and EMT-related genes were obtained from the Molecular Signatures database. The signature model was constructed using the least absolute shrinkage and selection operator Cox regression analysis in TCGA cohort. Validation data were obtained from the International Cancer Genome Consortium (ICGC) dataset of patients with HCC. Kaplan–Meier analysis and multivariate Cox analyses were employed to estimate the prognostic value. Immune status and tumor microenvironment were estimated using a single-sample gene set enrichment analysis (ssGSEA). The expression of prognostic genes was verified using qRT-PCR analysis of HCC cell lines.

Results
A signature model was constructed using EMT-related genes to determine HCC prognosis, based on which patients were divided into high-risk and low-risk groups. The risk score, as an independent factor, was related to tumor stage, grade, and immune cells infiltration. The results indicated that the most prognostic genes were highly expressed in the HCC cell lines, but GADD45B was down-regulated. Enrichment analysis suggested that immunoglobulin receptor binding and material metabolism were essential in the prognostic signature.

Conclusion
Our novel prognostic signature model has a vital impact on immune status and prognosis, significantly helping the decision-making related to the diagnosis and treatment of patients with HCC.
The Promise of Belonging: Racialized Youth Subject Positions in the Swedish Rural North
Authors: Goicolea Isabel , Gotfredsen Anne , Jonsson Frida , Wernesjö Ulrika 
Published: June 2022

AbstractThis article analyses how youth subject positions of the ‘racialized other’ are produced, and how these positions interconnect with the concept of belonging to the rural community. We do this by analysing 15 group discussions with 63 young people living in rural areas in northern Sweden taking a discursive psychology approach, and focusing on how discourses produce certain subject positions of ‘the racialized other’. Drawing on the concepts of the politics of belonging and the ‘stranger’, we argue that discourses on belonging to the (rural) community create boundaries that exclude ‘other’ youth, as well as resistance and contestation. The subject positions that such discourses produce represent racialized youth in stereotypical ways and imply a promise of belonging for certain ‘others’ based on their fulfilment of particular norms. However, such a depoliticized promise of belonging that places the responsibility for becoming integrated on the ‘others’ was also challenged. Firstly, in relation to criticisms of the welfare system, and secondly, in relation to racism as an unwelcome threat in rural communities.
A Music Cognition–Guided Framework for Multi-pitch Estimation
Authors: Li Xiaoquan , Yan Yijun , Soraghan John , Wang Zheng , Ren Jinchang 
Published: June 2022

AbstractAs one of the most important subtasks of automatic music transcription (AMT), multi-pitch estimation (MPE) has been studied extensively for predicting the fundamental frequencies in the frames of audio recordings during the past decade. However, how to use music perception and cognition for MPE has not yet been thoroughly investigated. Motivated by this, this demonstrates how to effectively detect the fundamental frequency and the harmonic structure of polyphonic music using a cognitive framework. Inspired by cognitive neuroscience, an integration of the constant Q transform and a state-of-the-art matrix factorization method called shift-invariant probabilistic latent component analysis (SI-PLCA) are proposed to resolve the polyphonic short-time magnitude log-spectra for multiple pitch estimation and source-specific feature extraction. The cognitions of rhythm, harmonic periodicity and instrument timbre are used to guide the analysis of characterizing contiguous notes and the relationship between fundamental frequency and harmonic frequencies for detecting the pitches from the outcomes of SI-PLCA. In the experiment, we compare the performance of proposed MPE system to a number of existing state-of-the-art approaches (seven weak learning methods and four deep learning methods) on three widely used datasets (i.e. MAPS, BACH10 and TRIOS) in terms of F-measure ($${F}_{1}$$F1) values. The experimental results show that the proposed MPE method provides the best overall performance against other existing methods.
Comparison of machine learning and process-based SWAT model in simulating streamflow in the Upper Indus Basin
Authors: Rahman Khalil Ur , Pham Quoc Bao , Jadoon Khan Zaib , Shahid Muhammad , Kushwaha Daniel Prakash , Duan Zheng , Mohammadi Babak , Khedher Khaled Mohamed , Anh Duong Tran 
Published: June 2022

AbstractThis study appraised and compared the performance of process-based hydrological SWAT (soil and water assessment tool) with a machine learning-based multi-layer perceptron (MLP) models for simulating streamflow in the Upper Indus Basin. The study period ranges from 1998 to 2013, where SWAT and MLP models were calibrated/trained and validated/tested for multiple sites during 1998–2005 and 2006–2013, respectively. The performance of both models was evaluated using nash–sutcliffe efficiency (NSE), coefficient of determination (R2), Percent BIAS (PBIAS), and mean absolute percentage error (MAPE). Results illustrated the relatively poor performance of the SWAT model as compared with the MLP model. NSE, PBIAS, R2, and MAPE for SWAT (MLP) models during calibration ranged from the minimum of 0.81 (0.90), 3.49 (0.02), 0.80 (0.25) and 7.61 (0.01) to the maximum of 0.86 (0.99), 9.84 (0.12), 0.87 (0.99), and 15.71 (0.267), respectively. The poor performance of SWAT compared with MLP might be influenced by several factors, including the selection of sensitive parameters, selection of snow specific sensitive parameters that might not represent actual snow conditions, potential limitations of the SCS-CN method used to simulate streamflow, and lack of SWAT ability to capture the hydropeaking in Indus River sub-basins (at Shatial bridge and Bisham Qila). Based on the robust performance of the MLP model, the current study recommends to develop and assess machine learning models and merging the SWAT model with machine learning models.
Identifikation von lernfördernden Maßnahmen zur Einführung von digitalen und assistiven Technologien (DAT) in Prozesse der pflegerischen Versorgung: eine qualitative Studie
Authors: Geist Lisa , Immenschuh Ursula , Jahn Patrick , Paulicke Denny , Zilezinski Max , Buhtz Christian , Hofstetter Sebastian 
Published: June 2022

Zusammenfassung
Hintergrund
Digitale und assistive Technologien (DAT) finden Eingang in die Versorgung. Konzepte, Pflegende strukturiert an die neuen Technologien heranzuführen, fehlen. Daher macht dieser Aufsatz einen Vorschlag, Pflegefachpersonen im Umgang mit DAT anzuleiten, zu beraten und zu schulen.

Ziel
Die Arbeit fragt, wie Pflegefachpersonen einen strukturierten Ansatz der Sensibilisierung, Qualifizierung und Erprobung hinsichtlich DAT erleben und bewerten. Verändert ein transformativer Lernansatz die Bereitschaft DAT einzusetzen?

Methode
Pflegende wurden hinsichtlich DAT sensibilisiert. Pflegende wurden in der Anwendung von 2 Robotiksystemen und eines passiven Exoskeletts geschult, um diese anschließend zu erproben. Das Erleben der strukturellen Ausgestaltung des Edukationsansatzes wurde durch Interviews und durch die qualitative Inhaltsanalyse nach Kuckartz eingeschätzt.

Ergebnisse
Alle 5 Pflegefachpersonen verfügen über eine 3‑jährige Ausbildung. Zwei nehmen neben pflegerischen auch Aufgaben der Wohnbereichsleitung wahr. Das Vorgehen wird durch alle Befragten positiv bewertet. Der strukturierte Ansatz erhöht das Interesse und die Bereitschaft DAT perspektivisch in den Pflegeprozess zu integrieren. Es zeigt sich, dass die Passgenauigkeit auf pflegerelevante Probleme und die Notwendigkeit DAT durch die Arbeitgeber verfügbar zu machen entscheidend sind, um DAT praktisch einzusetzen.

Schlussfolgerung
Ein strukturiertes Konzept erhöht die Einsatzbereitschaft von DAT in der pflegerischen Versorgung. Einer mangelhaften Implementierung von DAT liegen u. a. fehlendes Wissen und fehlende Aus-, Fort- und Weiterbildungskonzepte zugrunde. Die angestoßene Reflexion ermöglicht es DAT auf spezifische Pflegeprobleme zu prüfen, spezielle Situationen im Versorgungsprozess zu berücksichtigen und Anwendungshürden abzubauen.
Anaphylaxis to additives in vaccines
Authors: Mahler Vera , Junker Ann-Christine 
Published: June 2022

SummaryAnaphylaxis in connection with the administration of vaccines occurs only very rarely. Triggers of immunoglobulin IgE-mediated and non-IgE-mediated anaphylaxis—in addition to the active ingredient itself—may be excipients contained in the vaccine due to their special properties. Some of the excipients in medicinal products are the same compounds used as additives in food. Furthermore, residues from the manufacturing process (e.g., chicken egg white, casein, antibiotics, formaldehyde) or contaminants (e.g., from the primary packaging material) may be potential triggers of anaphylaxis in vaccines. This review article provides an overview of ingredients in vaccines that pose an allergenic risk potential. The components of COVID-19 vaccines approved and marketed in Germany are discussed with regard to their potential for triggering anaphylaxis and possible pathophysiological mechanisms involved.