bluuebunny/crossref_metadata_2025_split huggingface dataset:
UNER: Universal Named-Entity Recognition Framework
Authors: Alves Diego , Thakkar Gaurisha , Tadić Marko 
Published: November 2024

AbstractNamed-entity recognition and classification (NERC) is an essential natural language processing (NLP) task involved in many applications like interactive question answering, summarising, relation extraction, and text mining. Available NERC corpora follow different annotation schemes that vary in terms of formats and levels of complexity according to research requirements: from 1-level hierarchy annotations (e.g., “Person”, “Location”, and “Organisation”) to multi-level schemes. Inspired by the work of the Universal Dependencies framework in terms of a standard representation of parsed trees, we developed the universal named-entity recognition (UNER) framework, which consists of a multi-level NERC hierarchy and a corresponding workflow that parses data from Wikipedia and DBpedia, translating it to UNER annotations. This chapter presents the UNER hierarchy and its workflow for data extraction and annotation. The proposed process was used to generate an English corpus, which was evaluated qualitatively and quantitatively. Furthermore, seven strategies for annotation improvement were presented and discussed, showing that the usage of information from the Open Event Knowledge Graph (OEKG) can improve our dataset.
Conversational Question Answering over Knowledge Graphs
Authors: Kacupaj Endri , Singh Kuldeep , Maleshkova Maria , Lehmann Jens 
Published: November 2024

AbstractQuestion answering (QA) over knowledge graphs (KGs) is an essential task that maps a user’s utterance to a query over a KG to retrieve the correct answer. Earlier methods in this field relied heavily on predefined templates and rules, which had limited adaptability and learning capability. Recent research has made significant strides in answering straightforward questions, and there has been notable success in tackling more intricate queries as well. However, a key challenge remains that, often, a single round of question and answer is not enough. Users might have follow-up questions that delve deeper into a subject, relying on information from their initial queries. This situation is particularly common in conversational settings, where each new question might refer back to earlier topics or answers. In this chapter, we explore advanced techniques for handling such conversational QA over knowledge graphs. We leverage deep neural networks and multi-task learning approaches to create systems that can understand and respond to a series of interconnected questions. By focusing on these conversational aspects and the nuances between different types of queries, we aim to bridge a significant gap in current research, offering more dynamic and context-aware systems that can adapt to the evolving nature of human inquiry.
Targeting the Right Problem with Your Start-up: Uncovering Validation Techniques
Authors: Kuckertz Andreas , Leicht Thomas , Scheu Maximilian , da Silva Wagner Indra , Ebersberger Bernd 
Published: November 2024

AbstractIn this chapter, you will learn why validation is crucial throughout your start-up’s lifecycle, how to generate validated learning to inform entrepreneurial decision-making, and how to use validation to explore problems. We emphasize the importance of validating assumptions to avoid misjudging product ideas. By integrating the lean start-up framework and effectuation heuristics, we highlight the process of testing assumptions through customer feedback and iterative experimentation. We offer a generic validation blueprint comprising three steps—reflect, inquire, and learn—encouraging entrepreneurs to continuously validate their path toward achieving product/market fit and enhance their start-up’s chances of success. We offer advice for immediate action.
„Die beste Alkoholprävention ist die Antiemanzipation“
Authors: Balz Viola 
Published: November 2024

Zusammenfassung
Der Beitrag widmet sich aus einer geschlechterhistorischen Perspektive der Geschichte von sowie Diskussionen über einen konstatierten Anstieg von Frauenalkoholismus in der Bundesrepublik. Seit den 1950er Jahren beklagt der psychiatrische, pädagogische und psychologische Diskurs einen zunehmenden weiblichen Alkoholkonsum und macht die Frauenemanzipation als dessen Ursache aus. Der Artikel beleuchtet die männlich dominierten Debatten über Frauenalkoholismus bis 1968 sowie anschließend einsetzende feministische Kritiken. Er analysiert die in den Diskussionen über „die trinkende Frau“ zum Ausdruck kommenden Veränderungen der gesellschaftlichen Rolle von Frauen sowie zeitgleich sich formierende wissenschaftlich-patriarchale Gegenbewegungen. Dabei zeigt der Beitrag zum einen, wie ein klassischer Suchtbegriff aufgrund des Scheiterns medizinischer Behandlungsversuche erodiert und durch neues psychosoziales Erklärungswissen ersetzt wird. Zum anderen verdeutlicht er, wie die Frauenselbsthilfe sich dieses Wissen aneignet und neu interpretiert.
Trajectory of beta cell function and insulin clearance in stage 2 type 1 diabetes: natural history and response to teplizumab
Authors: Galderisi Alfonso , Sims Emily K. , Evans-Molina Carmella , Petrelli Alessandra , Cuthbertson David , Nathan Brandon M. , Ismail Heba M. , Herold Kevan C. , Moran Antoinette 
Published: November 2024

Abstract

Aims/hypothesis
We aimed to analyse TrialNet Anti-CD3 Prevention (TN10) data using oral minimal model (OMM)-derived indices to characterise the natural history of stage 2 type 1 diabetes in placebo-treated individuals, to describe early metabolic responses to teplizumab and to explore the predictive capacity of OMM measures for disease-free survival rate.

Methods
OMM-estimated insulin secretion, sensitivity and clearance and the disposition index were evaluated at baseline and at 3, 6 and 12 months post randomisation in placebo- and teplizumab-treated groups, and, within each group, in slow- and rapid-progressors (time to stage 3 disease >2 or

$$\le$$

≤

2 years). OMM metrics were also compared with the standard AUC C-peptide. Percentage changes in CD8+ T memory cell and programmed death-1 (PD-1) expression were evaluated in each group.

Results
Baseline metabolic characteristics were similar between 28 placebo- and 39 teplizumab-treated participants. Over 12 months, insulin secretion declined in placebo-treated and rose in teplizumab-treated participants. Within groups, placebo slow-progressors (n=14) maintained insulin secretion and sensitivity, while both declined in placebo rapid-progressors (n=14). Teplizumab slow-progressors (n=28) maintained elevated insulin secretion, while teplizumab rapid-progressors (n=11) experienced mild metabolic decline. Compared with rapid-progressor groups, insulin clearance significantly decreased between baseline and 3, 6 and 12 months in the slow-progressor groups in both treatment arms. In aggregate, both higher baseline insulin secretion (p=0.027) and reduced 12 month insulin clearance (p=0.045) predicted slower progression. A >25% loss of insulin secretion at 3 months had specificity of 0.95 (95% CI 0.86, 1.00) to identify rapid-progressors and correctly classified the 2 year risk for progression in 92% of participants, with a sensitivity of 0.19 (95% CI 0.08, 0.30). OMM-estimated insulin secretion outperformed AUC C-peptide to differentiate groups by treatment or to predict progression. Metabolic changes were paralleled by relative frequency of change in PD-1+ CD8+ T effector memory cells.

Conclusions/interpretation
OMM measures characterise the metabolic heterogeneity in stage 2 diabetes, identifying differences between rapid- and slow-progressors, and heterogeneous impacts of immunotherapy, suggesting the need to account for these differences when designing and interpreting clinical trials.

Graphical Abstract
Model design in data science: engineering design to uncover design processes and anomalies
Authors: Bordas Antoine , Le Masson Pascal , Weil Benoit 
Published: November 2024

Abstract
In the current data-rich environment, valorizing of data has become a common task in data science and requires the design of a statistical model to transform input data into a desirable output. The literature in data science regarding the design of new models is abundant, while in parallel, other streams of literature such as epistemology of science, has shown the relevance of anomalies in model design processes. Anomalies are to be understood as unexpected observations in data, an historical example being the discovery of Mercury based on its famous anomalous precession perihelion. Therefore, this paper addresses the various design processes in data science and their relationships to anomalies. To do so, we conceptualize what designing a data science model means, and we derive three design processes based on the latest theories in engineering design. This allows us to formulate assumptions regarding the relationships between each design process and anomalies, which we test with several case studies. Notably, three processes for the design of models in data science are identified and, for each of them, the following information is provided: (1) the various knowledge leveraged and generated and (2) the specific relations with anomalies. From a theoretical standpoint, this work is one of the first applications of design methods in data science. This work paves the way for more research at the intersection of engineering design and data science, which could enrich both fields.
Progressive degradation of acetylated wood by the brown rot fungi Coniophora puteana and Rhodonia placenta
Authors: Belt Tiina , Awais Muhammad 
Published: November 2024

Abstract
Acetylation is a wood modification method that reduces the hygroscopicity of wood and increases its resistance to degradation by wood decaying fungi. Even though acetylated wood can have very high decay resistance, the wood material can be degraded and sometimes deacetylated by fungi. This study investigated the degradation and deacetylation of acetylated wood by Coniophora puteana and Rhodonia placenta to better understand the relationship between degradation and deacetylation in two different brown rot fungi. Wood samples were exposed to the fungi in a stacked-sample decay test, followed by acetyl content measurements and FTIR spectroscopy to investigate chemical changes in the samples. The results showed that both fungi could degrade acetylated wood to high mass loss despite a strong reduction in moisture content, but only R. placenta was found to cause preferential deacetylation. The deacetylation was slight and only observed in the early stages of decay in highly acetylated wood. Otherwise, acetyl groups were lost from the samples at the rate of mass loss. FTIR spectroscopy confirmed the loss of acetyl groups and revealed some chemical differences between unacetylated and acetylated wood. The spectral data indicated the loss of acetyl groups from lignin, which suggests that the loss of acetyl groups is not only due to the degradation of acetylated carbohydrates. The degradation of acetylated wood required further investigation, but it is clear that extensive deacetylation is not a requirement for brown rot degradation.
Dopaminergic PET to SPECT domain adaptation: a cycle GAN translation approach
Authors: Lopes Leonor , Jiao Fangyang , Xue Song , Pyka Thomas , Krieger Korbinian , Ge Jingjie , Xu Qian , Fahmi Rachid , Spottiswoode Bruce , Soliman Ahmed , Buchert Ralph , Brendel Matthias , Hong Jimin , Guan Yihui , Bassetti Claudio L. A. , Rominger Axel , Zuo Chuantao , Shi Kuangyu , Wu Ping 
Published: November 2024

Abstract

Purpose
Dopamine transporter imaging is routinely used in Parkinson’s disease (PD) and atypical parkinsonian syndromes (APS) diagnosis. While [11C]CFT PET is prevalent in Asia with a large APS database, Europe relies on [123I]FP-CIT SPECT with limited APS data. Our aim was to develop a deep learning-based method to convert [11C]CFT PET images to [123I]FP-CIT SPECT images, facilitating multicenter studies and overcoming data scarcity to promote Artificial Intelligence (AI) advancements.

Methods
A CycleGAN was trained on [11C]CFT PET (n = 602, 72%PD) and [123I]FP-CIT SPECT (n = 1152, 85%PD) images from PD and non-parkinsonian control (NC) subjects. The model generated synthetic SPECT images from a real PET test set (n = 67, 75%PD). Synthetic images were quantitatively and visually evaluated.

Results
Fréchet Inception Distance indicated higher similarity between synthetic and real SPECT than between synthetic SPECT and real PET. A deep learning classification model trained on synthetic SPECT achieved sensitivity of 97.2% and specificity of 90.0% on real SPECT images. Striatal specific binding ratios of synthetic SPECT were not significantly different from real SPECT. The striatal left-right differences and putamen binding ratio were significantly different only in the PD cohort. Real PET and real SPECT had higher contrast-to-noise ratio compared to synthetic SPECT. Visual grading analysis scores showed no significant differences between real and synthetic SPECT, although reduced diagnostic performance on synthetic images was observed.

Conclusion
CycleGAN generated synthetic SPECT images visually indistinguishable from real ones and retained disease-specific information, demonstrating the feasibility of translating [11C]CFT PET to [123I]FP-CIT SPECT. This cross-modality synthesis could enhance further AI classification accuracy, supporting the diagnosis of PD and APS.
On the Löwner-John Ellipsoids of the Metric Polytope
Authors: Gartsman Raziel , Linial Nati 
Published: November 2024

AbstractThe collection of all n-point metric spaces of diameter $$\le 1$$

≤
1

constitutes a polytope $$\mathcal {M}_n \subset \mathbb {R}^{\left( {\begin{array}{c}n\\ 2\end{array}}\right) }$$

M
n

⊂

R

n

2

, called the Metric Polytope. In this paper, we consider the best approximations of $$\mathcal {M}_n$$

M
n

by ellipsoids. We give an exact explicit description of the largest volume ellipsoid contained in $$\mathcal {M}_n$$

M
n

. When inflated by a factor of $$\Theta (n)$$

Θ
(
n
)

, this ellipsoid contains $$\mathcal {M}_n$$

M
n

. It also turns out that the least volume ellipsoid containing $$\mathcal {M}_n$$

M
n

is a ball. When shrunk by a factor of $$\Theta (n)$$

Θ
(
n
)

, the resulting ball is contained in $$\mathcal {M}_n$$

M
n

. We note that the general theorems on such ellipsoid posit only that the pertinent inflation/shrinkage factors can be made as small as $$O(n^2)$$

O
(

n
2

)

.
Refugee mothers’ mental health in Denmark: possibilities and limits of home visiting programs
Authors: Marti-Castaner Maria , Poulsen Vivian Rueskov , Di Nucci Ezio , Villadsen Sarah Fredsted 
Published: November 2024

Abstract
Purpose
To explore the experiences of refugee mothers and community health nurses participating in a nurse home visiting program in Denmark, focusing on the program’s effects on the psychosocial well-being of refugee mothers during the transition to motherhood.

Methods
The nurse home visiting program was an add-on the public care offered to all families, with extra training of the community health nurses and more time to engage with the families with immigrant and refugee backgrounds. Community health nurses (12) and participating women (9) participated in qualitative interviews between September and December 2020, following the program’s conclusion.

Results
Utilizing the Resource-Based Model of refugee adaptation as a theoretical framework, we identified four main themes: (i) negotiating parenting norms and gaining confidence through parenting resources; (ii) finding emotional support to cope with integration pressures; (iii) expanding social resources, (iv) building bridges with welfare state services. These themes captured the resources gained by mothers through the home visiting program, positively influencing their psychosocial well-being, while also acknowledging the impact of the socio-political context on community health nurses’ work and mothers’ daily lives.

Conclusion
Findings offer insights about the potential and limitations of tailored nurse home visiting programs for refugee families, emphasizing the positive impact on mental health. However, challenges such as assimilation pressures, unwelcoming immigration policies, and discrimination may hinder program effectiveness.
Ultrasonic renal length as an indicator of renal fibrosis severity in non-diabetic patients with chronic kidney disease
Authors: Chen Ziman , Jiang Jun , Gunda Simon Takadiyi , Han Xinyang , Wu Chaoqun , Ying Michael Tin Cheung , Chen Fei 
Published: November 2024

Abstract
Background
Debate continues regarding the potential of the ultrasonic renal length to serve as an indicator for evaluating the advancement of renal fibrosis in chronic kidney disease (CKD). This study investigates the independent association between renal length and renal fibrosis in non-diabetic CKD patients and assesses its diagnostic performance.

Methods
From April 2019 to December 2021, 144 non-diabetic patients diagnosed with CKD who underwent a renal ultrasound examination and kidney biopsy were prospectively enrolled. Patients were categorized into the mild fibrosis group (n = 70) and the moderate-severe group (n = 74) based on the extent of fibrotic involvement. Ultrasonic renal length was measured from pole-to-pole in the coronal plane. A receiver operating characteristic (ROC) curve, multivariable logistic regression analysis, and a generalized additive model were performed.

Results
A negative linear correlation was found between renal length and moderate-severe renal fibrosis risk. Each centimeter increase in renal length decreased the odds of moderate-severe fibrosis by 38% (OR: 0.62; 95% CI 0.41–0.93; P = 0.020). After adjusting for confounders, the relationship persisted (OR: 0.58; 95% CI 0.33–1.00; P = 0.048). However, renal length presented limited discrimination ability in distinguishing degrees of renal fibrosis while controlling the key confounding factors, yielding an area under the ROC curve of only 0.58 (95% CI 0.45–0.70).

Conclusion
While an inverse relationship exists between renal length and risk of having moderate-severe renal fibrosis in non-diabetic CKD patients, renal length alone is insufficient for diagnosing fibrosis severity, underscoring the need for additional diagnostic parameters in CKD assessment.
The importance of socio-emotional skills obtained before the COVID-19 pandemic in supporting study engagement during the pandemic and transition to higher education
Authors: Mädamürk Kaja , Upadyaya Katja , Hietajärvi Lauri , Lonka Kirsti , Salmela-Aro Katariina 
Published: November 2024

AbstractThis study investigated the development of study engagement from the end of upper secondary school through the first and second years of higher education. The participants experienced the challenges related to the first wave of the COVID-19 pandemic while they were either university students or preparing for university entrance exams. The study employed a person-oriented approach to determine what kind of developmental trajectories emerge in study engagement when following the student participants from the end of upper secondary school through the first and second years of higher education. Furthermore, the study investigated whether socio-emotional skills obtained by the end of secondary school and before the pandemic play a role in more adaptive development through demanding restrictions related to the worldwide pandemic and general changes in the learning environment. The 852 participants answered questionnaires on study engagement and socio-emotional skills in spring 2019, and of them, 426 individuals who continued their education answered regarding study engagement again in spring 2020 and winter 2020/2021. The grades in math and Finnish language were also included. The results indicated that most students tended to experience a drop in study engagement during the first wave of COVID-19 compared to the pre-pandemic level; however, they managed to boost their engagement back to previous levels approximately 6 months later. Students who managed to recover their engagement also tended to have higher socio-emotional skills than students who were struggling with study engagement before the pandemic or who started to struggle during the pandemic.
Do Doctors Have a Responsibility to Challenge the Distorting Influence of Commerce on Healthcare Delivery? The Case of Assisted Reproductive Technology
Authors: Stanbury Craig , Kerridge Ian , Newson Ainsley J. , Ghinea Narcyz , Lipworth Wendy 
Published: November 2024

Abstract
Medicine has always existed in a marketplace, and there have been extensive discussions about the ethical implications of commerce in health care. For the most part, this discussion has focused on health professionals’ interactions with pharmaceutical and other health technology industries, with less attention given to other types of commercial influences, such as corporatized health services and fee-for-service practice. This is a significant lacuna because in many jurisdictions, some or all of healthcare is delivered in the private sector. Using the exemplar of Assisted Reproductive Technologies (ART), this paper asks: what, if any, responsibilities do doctors have to challenge the distorting influence of commerce in healthcare, other than those arising from their own interactions with health technology companies? ART provides a good focus for this question because it is an area of practice that has historically been provided in the private sector. First, we describe a range of concepts that offer helpful heuristics for capturing how and when doctors can reasonably be said to have responsibilities to resist commercial distortion, including: complicity, acquiescence, wilful ignorance, non-wilful ignorance, and duplicity. Second, we present ways that individual doctors can act to stop questionable behaviour on the part of their colleagues, clinics/corporations, and their profession. Third, we note that there are many situations where change cannot be achieved by individuals acting alone, and so we consider the responsibilities of health professionals as collectives as well as the role that professional bodies and regulators should play.