bluuebunny/crossref_metadata_2025_split huggingface dataset:
Taxonomy of machine learning paradigms: A data‐centric perspective
Authors: Emmert‐Streib Frank , Dehmer Matthias 
Published: June 2022

AbstractMachine learning is a field composed of various pillars. Traditionally, supervised learning (SL), unsupervised learning (UL), and reinforcement learning (RL) are the dominating learning paradigms that inspired the field since the 1950s. Based on these, thousands of different methods have been developed during the last seven decades used in nearly all application domains. However, recently, other learning paradigms are gaining momentum which complement and extend the above learning paradigms significantly. These are multi‐label learning (MLL), semi‐supervised learning (SSL), one‐class classification (OCC), positive‐unlabeled learning (PUL), transfer learning (TL), multi‐task learning (MTL), and one‐shot learning (OSL). The purpose of this article is a systematic discussion of these modern learning paradigms and their connection to the traditional ones. We discuss each of the learning paradigms formally by defining key constituents and paying particular attention to the data requirements for allowing an easy connection to applications. That means, we assume a data‐driven perspective. This perspective will also allow a systematic identification of relations between the individual learning paradigms in the form of a learning‐paradigm graph (LP‐graph). Overall, the LP‐graph establishes a taxonomy among 10 different learning paradigms.This article is categorized under:
Technologies > Machine Learning
Application Areas > Science and Technology
Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining
Beyond Data
Authors: Mantelero Alessandro 
Published: June 2022

AbstractIn a technology context dominated by data-intensive AI systems, the consequences of data processing are no longer restricted to the well-known privacy and data protection issues but encompass prejudices against a broader array of fundamental rights. Moreover, the tension between the extensive use of these systems, on the one hand, and the growing demand for ethically and socially responsible data use on the other, reveals the lack of a framework that can fully address the societal issues raised by AI.Against this background, neither traditional data protection impact assessment models nor the broader social or ethical impact assessment procedures appear to provide an adequate answer to the challenges of our algorithmic society. In contrast, a human rights-centred assessment may offer a better answer to the demand for a more comprehensive assessment, including not only data protection, but also the effects of data use on other fundamental rights and freedoms.Given the changes to society brought by technology and datafication, when applied to the field of AI the Human Rights Impact Assessment must then be enriched to consider ethical and societal issues, evolving into a more holistic Human Rights, Ethical and Social Impact Assessment (HRESIA), whose rationale and key elements are outlined in this chapter.
Weak gravity versus scale separation
Authors: Cribiori Niccolò , Dall’Agata Gianguido 
Published: June 2022

Abstract
We give evidence that fully supersymmetric Anti-de Sitter vacua of extended supergravity with a residual gauge group containing an abelian factor cannot be scale separated as a consequence of the weak gravity conjecture. We prove this for N = 2 and N = 8 supergravity and we explain how our argument applies also to vacua with partially broken, but extended residual supersymmetry. We finally discuss possible loopholes and especially how certain N = 1 models can evade our reasoning. Our results suggest that N = 0, 1 supersymmetry at the lagrangian level might be the most promising chances to obtain a truly four-dimensional effective description of quantum gravity.
Tip-end fusion of a rod-shaped secretory organelle
Authors: Naß Johannes , Koerdt Sophia N. , Biesemann Anja , Chehab Tarek , Yasuda Takao , Fukuda Mitsunori , Martín-Belmonte Fernando , Gerke Volker 
Published: June 2022

AbstractWeibel–Palade bodies (WPB) are elongated, rod-like secretory organelles unique to endothelial cells that store the pro-coagulant von-Willebrand factor (VWF) and undergo regulated exocytosis upon stimulation with Ca2+- or cAMP-raising agonists. We show here that WPB preferentially initiate fusion with the plasma membrane at their tips and identify synaptotagmin-like protein 2-a (Slp2-a) as a positive regulator of VWF secretion most likely mediating this topological selectivity. Following secretagogue stimulation, Slp2-a accumulates at one WPB tip before fusion occurs at this site. Depletion of Slp2-a reduces Ca2+-dependent secretion of highly multimeric VWF and interferes with the formation of actin rings at WPB–plasma membrane fusion sites that support the expulsion of the VWF multimers and most likely require a tip-end fusion topology. Phosphatidylinositol (4,5)-bisphosphate [PI(4,5)P2] binding via the C2A domain of Slp2-a is required for accumulation of Slp2-a at the tip ends of fusing WPB, suggesting that Slp2-a mediates polar exocytosis by initiating contacts between WPB tips and plasma membrane PI(4,5)P2.
Glycation of α-synuclein hampers its binding to synaptic-like vesicles and its driving effect on their fusion
Authors: Uceda Ana Belén , Frau Juan , Vilanova Bartolomé , Adrover Miquel 
Published: June 2022

AbstractParkinson’s disease (PD) is one of the most prevalent neurodegenerative disorders affecting the worldwide population. One of its hallmarks is the intraneuronal accumulation of insoluble Lewy bodies (LBs), which cause the death of dopaminergic neurons. α-Synuclein (αS) is the main component of these LBs and in them, it commonly contains non-enzymatic post-translational modifications, such as those resulting from its reaction with reactive carbonyl species arising as side products of the intraneuronal glycolysis (mainly methylglyoxal). Consequently, lysines of the αS found in LBs of diabetic individuals are usually carboxyethylated. A precise comprehension of the effect of Nε-(carboxyethyl)lysine (CEL) on the aggregation of αS and on its physiological function becomes crucial to fully understand the molecular mechanisms underlying the development of diabetes-induced PD. Consequently, we have here used a synthetic αS where all its Lys have been replaced by CEL moieties (αS-CEL), and we have studied how these modifications could impact on the neurotransmission mechanism. This study allows us to describe how the non-enzymatic glycosylation (glycation) affects the function of a protein like αS, involved in the pathogenesis of PD. CEL decreases the ability of αS to bind micelles, although the micelle-bound fraction of αS-CEL still displays an α-helical fold resembling that of the lipid-bound αS. However, CEL completely abolishes the affinity of αS towards synaptic-like vesicles and, consequently, it hampers its physiological function as a catalyst of the clustering and the fusion of the synaptic vesicles.
Essential role of CK2α for the interaction and stability of replication fork factors during DNA synthesis and activation of the S-phase checkpoint
Authors: Guerra Barbara , Doktor Thomas K. , Frederiksen Sabrina B. , Somyajit Kumar , Andresen Brage S. 
Published: June 2022

AbstractThe ataxia telangiectasia mutated and Rad3-related (ATR)-CHK1 pathway is the major signalling cascade activated in response to DNA replication stress. This pathway is associated with the core of the DNA replication machinery comprising CDC45, the replicative MCM2-7 hexamer, GINS (altogether forming the CMG complex), primase–polymerase (POLε, -α, and -δ) complex, and additional fork protection factors such as AND-1, CLASPIN (CLSPN), and TIMELESS/TIPIN. In this study, we report that functional protein kinase CK2α is critical for preserving replisome integrity and for mounting S-phase checkpoint signalling. We find that CDC45, CLSPN and MCM7 are novel CK2α interacting partners and these interactions are particularly important for maintenance of stable MCM7–CDC45, ATRIP–ATR–MCM7, and ATR–CLSPN protein complexes. Consistently, cells depleted of CK2α and treated with hydroxyurea display compromised replisome integrity, reduced chromatin binding of checkpoint mediator CLSPN, attenuated ATR-mediated S-phase checkpoint and delayed recovery of stalled forks. In further support of this, differential gene expression analysis by RNA-sequencing revealed that down-regulation of CK2α accompanies global shutdown of genes that are implicated in the S-phase checkpoint. These findings add to our understanding of the molecular mechanisms involved in DNA replication by showing that the protein kinase CK2α is essential for maintaining the stability of the replisome machinery and for optimizing ATR-CHK1 signalling activation upon replication stress.
Der Stellenwert gesundheitsbewusster Ernährungsbildung in der Schule
Authors: Prade Louisa , Richter Matthias , Stangl Gabriele I. , Hoßfeld Uwe , Fink Astrid , Knöchelmann Anja 
Published: June 2022

Zusammenfassung
Einleitung
Übergewicht, auch bei Kindern und Jugendlichen, stellt national wie international ein großes Problem dar, welches stark mit Ernährung verknüpft ist. Ernährungsgewohnheiten werden bereits früh geprägt und können Einfluss auf die Krankheitsentstehung nehmen. Schulen als Lern- und Lebensorte können dabei ausgewogene und nachhaltige Ernährungsgewohnheiten fördern. Ziel der vorliegenden Arbeit war daher die Analyse ausgewählter Lehrpläne zur Ernährungsbildung (EB), um darauf basierend Defizite und Verbesserungsvorschläge für die schulische EB herauszuarbeiten.

Methodik
Untersucht wurden naturwissenschaftliche und hauswirtschaftliche Rahmenlehrpläne weiterführender allgemeinbildender Schulen der neuen Bundesländer in der aktuellsten Version bis 2019 mittels qualitativer Lehrplananalyse. Im Fokus standen Ernährungsthemen sowie deren Vertiefungsmöglichkeiten, praktische Umsetzung und Zeitumfang.

Ergebnisse und Diskussion
Ernährung und Humanbiologie werden vorrangig bis Klasse 8 in allen Lehrplänen unterrichtet, komplexere Themen größtenteils ab Klasse 9. Konkrete alltagsrelevante Lerninhalte zu praktischen Ernährungsweisen, zur Lebensmittelqualität sowie zur Rolle der Ernährung für die Krankheitsprävention können die Ernährungskompetenzen der Schüler:innen maßgeblich verbessern, finden jedoch derzeit zu wenig Beachtung in den Lehrplänen. Die Hauswirtschaftsfächer thematisieren u. a. Verbraucherthemen, werden aber nicht an Gymnasien bzw. nicht in allen Bundesländern angeboten. Wahlbereiche und Leistungskurse können die EB ergänzen, sind aber nicht an allen Schulen Teil des Lehrplans. Der Zeitumfang und die praktische Umsetzung für die EB sind u. a. stark von schulinternen Faktoren abhängig. Es lassen sich teilweise erhebliche Defizite in der EB feststellen.

Schlussfolgerung
Als sinnvoll erachtet werden eine intensivierte EB in höheren Jahrgängen, die Einführung von Hauswirtschaftsfächern in allen Schulformen und eine Vereinheitlichung der Lehrplaninhalte zwischen den einzelnen Bundesländern.
Using machine learning to predict the density profiles of surface-densified wood based on cross-sectional images
Authors: Neyses Benedikt , Scharf Alexander 
Published: June 2022

AbstractOver the past decades, the surface densification of solid wood has received increased attention. However, the inhomogeneous density distribution in the densification direction might be a challenge with regard to process control within a large-scale production process, as the density profile governs many relevant properties of surface-densified wood. Currently, the measurement of density profiles relies on sensitive X-ray equipment and is difficult to integrate into an on-line process. Hence, in this study, three machine learning approaches were applied to predict the density profiles of surface-densified Scots pine specimens, only based on visual image acquisition—a technology that is ubiquitous in the wood industry: partial least squares (PLS) regression, artificial neural networks (ANN), and convolutional neural networks (CNN). The machine learning models were trained on images of the specimen cross-sections as input data, and X-ray density profiles as output data. There were 1850 observations, and the model performance was evaluated on external test sets. The models had mean absolute percentage errors of the predicted values between 9 and 18%; the CNN achieving the smallest error (9.24%). A deeper analysis of the data revealed that the ANN approach performed inconsistently between observations. PLS regression predicted the main density peak to a high accuracy but could not model other features. Only the CNN could reliably model the main density peak, wide growth rings, and the important region between the specimen surface and the main density peak. The ability of the models to generalise to untypical new data was improved by augmentation of the training data.
Breeding oat for resistance to the crown rust pathogen Puccinia coronata f. sp. avenae: achievements and prospects
Authors: Park R. F. , Boshoff W. H. P. , Cabral A. L. , Chong J. , Martinelli J. A. , McMullen M. S. , Fetch J. W. Mitchell , Paczos-Grzęda E. , Prats E. , Roake J. , Sowa S. , Ziems L. , Singh D. 
Published: June 2022

AbstractCrown rust, caused byPuccinia coronataf. sp.avenae(Pca), is a significant impediment to global oat production. Some 98 alleles at 92 loci conferring resistance toPcainAvenahave been designated; however, allelic relationships and chromosomal locations of many of these are unknown. Long-term monitoring ofPcain Australia, North America and elsewhere has shown that it is highly variable even in the absence of sexual recombination, likely due to large pathogen populations that cycle between wild oat communities and oat crops. Efforts to develop cultivars with genetic resistance toPcabegan in the 1950s. Based almost solely on all all-stage resistance, this has had temporary benefits but very limited success. The inability to eradicate wild oats, and their common occurrence in many oat growing regions, means that future strategies to controlPcamust be based on the assumption of a large and variable prevailing pathogen population with high evolutionary potential, even if cultivars with durable resistance are deployed and grown widely. The presence of minor gene, additive APR toPcain hexaploid oat germplasm opens the possibility of pyramiding several such genes to give high levels of resistance. The recent availability of reference genomes for diploid and hexaploid oat will undoubtedly accelerate efforts to discover, characterise and develop high throughput diagnostic markers to introgress and pyramid resistance toPcain high yielding adapted oat germplasm.
Depression and anxiety prevalence in people with cystic fibrosis and their caregivers: a systematic review and meta-analysis
Authors: Lord Louise , McKernon David , Grzeskowiak Luke , Kirsa Sue , Ilomaki Jenni 
Published: June 2022

Abstract
Background
Prevalence of depression and anxiety in people with cystic fibrosis (PwCF) and their caregivers is high, however, results have been inconsistent. This systematic review and meta-analysis aimed to estimate the prevalence of depression and anxiety in PwCF and their caregivers and explore sources of heterogeneity.

Method
MEDLINE, EMBASE, CINAHL plus and PsychINFO databases were searched from inception to January 2021. Studies were included if a specific psychometric tool (PT) to assess depression or anxiety (rather than quality of life) was used and did not involve a transitory patient state. Random-effects models were applied due to high anticipated heterogeneity and I2 estimates were calculated. Sources of heterogeneity were explored through subgroup comparisons. The presence of small-study effects was investigated visually using funnel plots and statistically using the Egger test.

Results
A total of 94 articles (48 full-text publications, 46 abstracts) were included. Depression prevalence in adolescents aged 12–18 years (n = 2386), adults (n = 9206) and caregivers (n = 6617) were 18.7% (95% CI 12.8–25.3%, I2 = 89.2%), 27.2% (95% CI 23.6–31%, I2 = 90.4%), and 32.8% (95% CI 27.9–37.9%, I2 = 90.3%), respectively. Anxiety prevalence in adolescents aged 12–18 years (n = 2142) was 26% (95% CI 19.6–33%, I2 = 86.4%), 28.4% (95% CI 25–31.9%, I2 = 85%) for adults (n = 8175), and 38.4% (95% CI 30.8–46.2%, I2 = 94.6%) for caregivers (n = 5931). Prevalence differed by the PT used and study location.

Discussion
This comprehensive analysis found the prevalence of depression and anxiety in PwCF and their caregivers to be high, supporting recommendations for regular screening. Choice of PT significantly influenced prevalence, indicating a need for future studies to identify the optimal PT for each CF population to identify those most at risk.
Redefining culture in cultural robotics
Authors: Ornelas Mark L. , Smith Gary B. , Mansouri Masoumeh 
Published: June 2022

AbstractCultural influences are pervasive throughout human behaviour, and as human–robot interactions become more common, roboticists are increasingly focusing attention on how to build robots that are culturally competent and culturally sustainable. The current treatment of culture in robotics, however, is largely limited to the definition of culture as national culture. This is problematic for three reasons: it ignores subcultures, it loses specificity and hides the nuances in cultures, and it excludes refugees and stateless persons. We propose to shift the focus of cultural robotics to redefine culture as an emergent phenomenon. We make use of three research programmes in the social and cognitive sciences to justify this definition. Consequently, cultural behaviour cannot be explicitly programmed into a robot, rather, a robot must be designed with the capability to participate in the interactions that lead to the arising of cultural behaviour. In the final part of the paper, we explore which capacities and abilities are the most salient for a robot to do this.
Identification of housekeeping genes of Candidatus Branchiomonas cysticola associated with epitheliocystis in Atlantic salmon (Salmo salar L.)
Authors: Mjølnerød Even Bysveen , Srivastava Aashish , Moore Lindsey J. , Plarre Heidrun , Nylund Are 
Published: June 2022

AbstractCandidatus Branchiomonas cysticola is an intracellular, gram-negative Betaproteobacteria causing epitheliocystis in Atlantic Salmon (Salmo salar L.). The bacterium has not been genetically characterized at the intraspecific level despite its high prevalence among salmon suffering from gill disease in Norwegian aquaculture. DNA from gill samples of Atlantic salmon PCR positive for Cand. B. cysticola and displaying pathological signs of gill disease, was, therefore, extracted and subject to next-generation sequencing (mNGS). Partial sequences of four housekeeping (HK) genes (aceE, lepA, rplB, rpoC) were ultimately identified from the sequenced material. Assays for real-time RT-PCR and fluorescence in-situ hybridization, targeting the newly acquired genes, were simultaneously applied with existing assays targeting the previously characterized 16S rRNA gene. Agreement in both expression and specificity between these putative HK genes and the 16S gene was observed in all instances, indicating that the partial sequences of these HK genes originate from Cand. B. cysticola. The knowledge generated from the present study constitutes a major prerequisite for the future design of novel genotyping schemes for this bacterium.
Minority report: small-scale metagenomic analysis of the non-bacterial kitchen sponge microbiota
Authors: Brandau Lena , Jacksch Susanne , Weis Severin , Schnell Sylvia , Egert Markus 
Published: June 2022

AbstractKitchen sponges are particularly well known to harbor a high number and diversity of bacteria, including pathogens. Viruses, archaea, and eukaryotes in kitchen sponges, however, have not been examined in detail so far. To increase knowledge on the non-bacterial kitchen sponge microbiota and its potential hygienic relevance, we investigated five used kitchen sponges by means of metagenomic shot-gun sequencing. Viral particles were sought to be enriched by a filter step during DNA extraction from the sponges. Data analysis revealed that ~ 2% of the sequences could be assigned to non-bacterial taxa. Each sponge harbored different virus (phage) species, while the present archaea were predominantly affiliated with halophilic taxa. Among the eukaryotic taxa, besides harmless algae, or amoebas, mainly DNA from food-left-overs was found. The presented work offers new insights into the complex microbiota of used kitchen sponges and contributes to a better understanding of their hygienic relevance.
Machine learning-based protein crystal detection for monitoring of crystallization processes enabled with large-scale synthetic data sets of photorealistic images
Authors: Bischoff Daniel , Walla Brigitte , Weuster-Botz Dirk 
Published: June 2022

AbstractSince preparative chromatography is a sustainability challenge due to large amounts of consumables used in downstream processing of biomolecules, protein crystallization offers a promising alternative as a purification method. While the limited crystallizability of proteins often restricts a broad application of crystallization as a purification method, advances in molecular biology, as well as computational methods are pushing the applicability towards integration in biotechnological downstream processes. However, in industrial and academic settings, monitoring protein crystallization processes non-invasively by microscopic photography and automated image evaluation remains a challenging problem. Recently, the identification of single crystal objects using deep learning has been the subject of increased attention for various model systems. However, the advancement of crystal detection using deep learning for biotechnological applications is limited: robust models obtained through supervised machine learning tasks require large-scale and high-quality data sets usually obtained in large projects through extensive manual labeling, an approach that is highly error-prone for dense systems of transparent crystals. For the first time, recent trends involving the use of synthetic data sets for supervised learning are transferred, thus generating photorealistic images of virtual protein crystals in suspension (PCS) through the use of ray tracing algorithms, accompanied by specialized data augmentations modelling experimental noise. Further, it is demonstrated that state-of-the-art models trained with the large-scale synthetic PCS data set outperform similar fine-tuned models based on the average precision metric on a validation data set, followed by experimental validation using high-resolution photomicrographs from stirred tank protein crystallization processes.