bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differential response to neoadjuvant endocrine therapy for Black/African American and White women in NCDB
Authors: Jones Veronica , Schroeder Mary C. , Roberson Mya L. , De Andrade James , Lizarraga Ingrid M. 
Published: September 2023

Abstract
Purpose
Compared to White women, there are higher mortality rates in Black/African American (BAA) women with hormone receptor-positive breast cancer (HR + BC) which may be partially due to differences in treatment resistance. We assessed factors associated with response to neoadjuvant endocrine therapy (NET).

Methods
The National Cancer Database (NCDB) was queried for women with clinical stage I–III HR + BC diagnosed 2006–2017 and treated with NET. Univariate and multivariate analyses described associations between the sample, duration of NET, and subsequent treatment response, defined by changes between clinical and pathological staging.

Results
The analytic sample included 9864 White and 1090 BAA women. Compared to White women, BAA women were younger, had more co-morbidities, were higher stage at presentation, and more likely to have > 24 weeks of NET. After excluding those with unknown pT/N/M, 3521 White and 365 BAA women were evaluated for NET response. On multivariate analyses, controlling for age, stage, histology, HR positivity, and duration of NET, BAA women were more likely to downstage to pT0/Tis (OR 3.0, CI 1.2–7.1) and upstage to Stage IV (OR 2.4, CI 1.002–5.6). None of the women downstaged to pT0/Tis presented with clinical stage III disease; only 2 of the women upstaged to Stage IV disease presented with clinical Stage I disease.

Conclusion
Independent of NET duration and clinical stage at presentation, BAA women were more likely to experience both complete tumor response and progression to metastatic disease. These results suggest significant heterogeneity in tumor biology and warrant a more nuanced therapeutic approach to HR + BC.
‘It could have been us’. Peer responses to money-laundering violations in the Dutch banking industry
Authors: Merz Anna 
Published: September 2023

AbstractMuch literature has focused on societal responses to corporate scandals, either by authorities or the public. However, there is little research on responses to corporate deviance by peers (corporations in the same industry). As corporations face a Zeitgeist characterised by increased attention to, and disapproval of, corporate deviance, they are compelled to respond to the external ‘labelling’ of their behaviour, as well as that of their peers. In this context of increasing public scrutiny, this article explores how (employees at) corporations respond to deviant peer behaviour. To examine this question, the case study of non-compliance with anti-money laundering (AML) regulations in the Dutch banking industry is utilised. Six stages of peer interactions were identified, namely, panic and fear, comparing practices, distancing, investing, and cooperation and defiance. In these six stages, condemnation between peers is incidental and mainly functions as a tool to guard their reputation (defence mechanism). Peer responses are determined by characteristics of the act (severance of the violation), actor (comparability and identification as peers), the audience (type of enforcement and public attention), and the situation (knowledge on the violation). As AML cases spread become more frequent across the industry, defence mechanisms also expand, thereby resulting in cooperation between banks and defiance of regulators.
Digital modes of interpretation of Pictish sculpture
Authors: Pisani Sharon , Miller Alan , Hall Mark 
Published: September 2023

AbstractCultural heritage is no longer something that can only be experienced in a museum exhibition. Digital tools have facilitated the distribution of material relating to artefacts, both in its representation and in presenting its context. This paper describes how digital modelling techniques can be synthesised with 3D scanning to digitally restore artefacts and create authentic replicas of their original states. The digital artefacts can then be used to assist the process of interpreting these artefacts in diverse forms, both in the museum and outside the museum. The study looks at Pictish sculpture as a case-study, restoring 3D models of two stones, and creating varying opportunities for their interpretation. As part of this study, new interactive tools, a virtual reality environment, and a virtual tour are built to assist immersive interpretation of the Pictish sculpture. The application of these digitised objects serves as an opportunity for informal learning. These applications were evaluated during a drop-in session. Findings show that all participants enjoyed the immersive mode of learning with 89% also showing a willingness to learn more about the topic.
Grasping hold of functional trade-offs using the diversity of foot forms in Australian birds
Authors: Martin Ellen M. , Sherratt Emma 
Published: September 2023

AbstractThe remarkable diversity of ecological niches that birds have evolved to inhabit have resulted in their status as model organisms to study how the same morphological features can adapt to different environments. Not least of these features is the avian foot, which has diversified into a wide range of forms suited to several different ecological functions. In this investigation, we examine how a potential trade-off between two such functions is expressed in the foot morphology of the Australian avifauna; namely, the impact that specialising for either walking or grasping has on the proportions of the phalanges. The lengths of the body, foot, third digit and its phalanges, and the hallux were recorded from 106 preserved skins belonging to 22 species. Our analysis of these data shows that this functional specialisation presents a similar morphological gradient in Australian birds as has been previously observed in American species, with a few unique exceptions. Generally, species that are reliant on the foot to grasp (e.g., perching and gripping prey) display greater distal phalanx and hallux lengths than species that are specialised for walking or wading. However, the terrestrial Megapodes of Australia demonstrate a more intermediate morphology, potentially as a result of the unique mound construction behaviour occurring in this clade. These findings have relevance not only for use in identifying the ecology of cryptic or extinct species from morphology, but also for determining future evolutionary changes in different avian groups.
Raw water transfers: why a global freshwater invasion pathway has been overlooked
Authors: Waine Ava , Robertson Peter , Pattison Zarah 
Published: September 2023

AbstractZhu et al. (Science 380:1230, 2023, https://doi.org/10.1126/science.adi6022) recently reported in Science that ‘water diversions’ carry a range of freshwater invasive non-native species (INNS) in China, and make calls for the Chinese government to take actions to monitor this invasion pathway and prevent future spread. This issue is not confined to China however. Water diversions, more commonly known internationally as ‘water transfers’ or ‘raw water transfers’, exist globally in large numbers. Despite worldwide occurrence, this major invasion pathway has received little attention within the field of freshwater ecology or invasion ecology, beyond a limited number of regional studies which offer little context regarding the global nature of the pathway. We discuss the factors contributing to the widespread lack of awareness of this uniquely complex invasion pathway, and emphasise the importance of future collaboration and knowledge sharing in this emerging field. Transdisciplinary research is needed to develop effective management techniques for this invasion pathway and ensure that the threat to global freshwater biodiversity posed by INNS is dealt with comprehensively.
The Apple Doesn’t Fall Far from the Tree? Paranoia and Safety Behaviours in Adolescent-Parent-Dyads
Authors: Schönig Sven N. , Thompson Elizabeth , Kingston Jessica , Gaudiano Brandon A. , Ellett Lyn , Krkovic Katarina 
Published: September 2023

AbstractParanoia is a common experience in adolescence that may entail the use of safety behaviours (e.g. avoidance), which are assumed to maintain paranoia in the long run. As the development of paranoia and related safety behaviours in youth may be influenced by their caregivers, we aimed to investigate the associations of paranoia and safety behaviours in adolescents and their parents. Adolescents from the general population aged 14–17 and one of their parents (N = 142 dyads) were recruited via Qualtrics to complete online surveys including measures of paranoia, safety behaviour use, anxiety, and demographics. We fitted an Actor-Partner-Interdependence Model (APIM) for testing dyadic parent–child interaction by using structural equation modelling and controlled for adolescents’ and parents’ anxiety. Results indicated that paranoia positively predicted safety behaviour use in adolescents and in parents. There were significant positive intra-dyad (i.e. parent-adolescent) correlations for both paranoia and safety behaviour use. One partner effect was significant: parental paranoia positively predicted the safety behaviour use of their adolescent child. Conversely, adolescents’ paranoia did not predict their parents’ safety behaviour use. Our findings corroborate prior research demonstrating an association between paranoia and safety behaviours among adults, and extend this association to adolescents. Children of parents experiencing paranoia are at increased risk of developing paranoia and safety behaviours, which indicates the need for interventions that target paranoia and safety behaviours in family systems.
Generalized Pitchfork Bifurcations in D-Concave Nonautonomous Scalar Ordinary Differential Equations
Authors: Dueñas Jesús , Núñez Carmen , Obaya Rafael 
Published: September 2023

AbstractThe global bifurcation diagrams for two different one-parametric perturbations ($$+\lambda x$$

+
λ
x

and $$+\lambda x^2$$

+
λ

x
2

) of a dissipative scalar nonautonomous ordinary differential equation $$x'=f(t,x)$$

x
′

=
f

(
t
,
x
)

are described assuming that 0 is a constant solution, that f is recurrent in t, and that its first derivative with respect to x is a strictly concave function. The use of the skewproduct formalism allows us to identify bifurcations with changes in the number of minimal sets and in the shape of the global attractor. In the case of perturbation $$+\lambda x$$

+
λ
x

, a so-called generalized pitchfork bifurcation may arise, with the particularity of lack of an analogue in autonomous dynamics. This new bifurcation pattern is extensively investigated in this work.
Implicit Integration of Nonlinear Evolution Equations on Tensor Manifolds
Authors: Rodgers Abram , Venturi Daniele 
Published: September 2023

AbstractExplicit step-truncation tensor methods have recently proven successful in integrating initial value problems for high-dimensional partial differential equations. However, the combination of non-linearity and stiffness may introduce time-step restrictions which could make explicit integration computationally infeasible. To overcome this problem, we develop a new class of implicit rank-adaptive algorithms for temporal integration of nonlinear evolution equations on tensor manifolds. These algorithms are based on performing one time step with a conventional time-stepping scheme, followed by an implicit fixed point iteration step involving a rank-adaptive truncation operation onto a tensor manifold. Implicit step truncation methods are straightforward to implement as they rely only on arithmetic operations between tensors, which can be performed by efficient and scalable parallel algorithms. Numerical applications demonstrating the effectiveness of implicit step-truncation tensor integrators are presented and discussed for the Allen–Cahn equation, the Fokker–Planck equation, and the nonlinear Schrödinger equation.
Implementation of a Patient Summary Web Application According to the International Patient Summary and Validation in Common Use Cases in Japan
Authors: Song Chong , Nakayama Masaharu 
Published: September 2023

Abstract
Background
The application of standardized patient summaries would reduce the risk of information overload and related problems for physicians and nurses. Although the International Patient Summary (IPS) standard has been developed, disseminating its applications has challenges, including data conversion of existing systems and development of application matching with common use cases in Japan. This study aimed to develop a patient summary application that summarizes and visualizes patient information accumulated by existing systems.

Methods
We converted clinical data from the Standardized Structured Medical Information eXchange version 2 (SS-MIX2) storage at Tohoku University Hospital into the Health Level 7 Fast Healthcare Interoperability Resource (FHIR) repository. Subsequently, we implemented a patient summary web application concerning the IPS and evaluated 12 common use cases of the discharge summary.

Results
The FHIR resources of seven of the necessary IPS sections were successfully converted from existing SS-MIX2 data. In the main view of the application we developed, all the minimum necessary patient information was summarized and visualized. All types of mandatory or required sections in the IPS and all structured information items of the discharge summary were displayed. Of the discharge summary, 75% of sections and 61.7% of information items were completely displayed, matching 12 common use cases in Japan.

Conclusions
We implemented a patient summary application that summarizes and visualizes patient information accumulated by existing systems and is evaluated in common use cases in Japan. Efficient sharing of the minimum necessary patient information for physicians is expected to reduce information overload, workload, and burnout.
Equity, Imagination and Contested Narratives
Authors: Kirk-Smith Adam 
Published: September 2023

AbstractJustice and the idea of the moral good pervade legal philosophy and underlie much of legal practice in different contexts. They are particularly resonant in the law of equity and the remedies it makes available. This article uses equity and conceptions of justice explores the role of narratives, fairness and values through the lens of the constructive trust, science fiction, temporality, the counterfactual imagination and creativity. This special edition’s theme of intersectionalities within law is a central analytical thread. Power dynamics and the place of equity in social dialogues around justice and fairness are set alongside socioeconomic vulnerability and othering in understanding how the law succeeds and fails in managing emerging inequalities. A lack of autonomy and voicelessness is often revealed through constrained access to law and legal services, as well as a more vulnerable relationship with time. Engaging the constructive trust provides interesting opportunities to examine the role of the trust within law, and through that explore wider discussions about the nature of legal systems and the remedies they may give rise to. Science fiction has always provided opportunities to create counterfactual worlds and engage hypothetical questions, many of which might illuminate contemporary debates or resonate forward to emerging concerns. Imagination is a central tenet of these worlds, as well as, increasingly, within law when faced with emerging technologies and the issues they present. The article concludes with an acknowledgement that such narratives and opportunities to question social norms can be a valuable tool in grounding societal change.
Terahertz imaging technology for localization of cancer tumours: a technical review
Authors: Gezimati M. , Singh Ghanshyam 
Published: September 2023

AbstractCurrently, cancer is a large contributing factor in the increased mortality rates and at present the predictions are estimating an increased trend. The conventional medical cancer imaging modalities, for example X-Ray and Computed Tomography use ionizing radiation which is not tissue friendly for repeated assessments. The Terahertz (THz) cancer imaging offers novel opportunities for non-ionizing, non-invasive and early cancer detection, or diagnosis as well as improved cancer patient treatment follow-ups. In this review, a broad overview is given on the potential of THz radiation-based imaging and sensing as a technique for detection of various cancers cells. The THz radiation dynamics and interaction mechanisms with biological systems as well as parameter extraction and modelling for the observed THz image contrast are studied. The experimental studies on THz imaging and sensing are investigated with the goal approach to investigate the ex vivo, in vitro, and in vivo observations. The use of advanced analytic algorithms, specifically deep learning, is proposed for improved detection, discrimination of complex tissue with overlapping dielectric properties and development of clinical decision support systems. Research gaps in the THz imaging studies are identified based on recent trends, latest strategies suggested and the roadmap for future research direction provided.
XCovNet: An optimized xception convolutional neural network for classification of COVID-19 from point-of-care lung ultrasound images
Authors: Madhu G. , Kautish Sandeep , Gupta Yogita , Nagachandrika G. , Biju Soly Mathew , Kumar Manoj 
Published: September 2023

AbstractGlobal livelihoods are impacted by the novel coronavirus (COVID-19) disease, which mostly affects the respiratory system and spreads via airborne transmission. The disease has spread to almost every nation and is still widespread worldwide. Early and reliable diagnosis is essential to prevent the development of this highly risky disease. The computer-aided diagnostic model facilitates medical practitioners in obtaining a quick and accurate diagnosis. To address these limitations, this study develops an optimized Xception convolutional neural network, called "XCovNet," for recognizing COVID-19 from point-of-care ultrasound (POCUS) images. This model employs a stack of modules, each of which has a slew of feature extractors that enable it to learn richer representations with fewer parameters. The model identifies the presence of COVID-19 by classifying POCUS images containing Coronavirus samples, viral pneumonia samples, and healthy ultrasound images. We compare and evaluate the proposed network with state-of-the-art (SOTA) deep learning models such as VGG, DenseNet, Inception-V3, ResNet, and Xception Networks. By using the XCovNet model, the previous study's problems are cautiously addressed and overhauled by achieving 99.76% accuracy, 99.89% specificity, 99.87% sensitivity, and 99.75% F1-score. To understand the underlying behavior of the proposed network, different tests are performed on different shuffle patterns. Thus, the proposed "XCovNet" can, in regions where test kits are limited, be used to help radiologists detect COVID-19 patients through ultrasound images in the current COVID-19 situation.
Network flow problem heuristic reduction using machine learning
Authors: Rosecký M. , Pluskal J. , Šomplák R. 
Published: September 2023

AbstractMost of the supporting tools developed for logistic optimization and processing infrastructure planning are based on the network flow problem. The real-world application of these instruments can provide great insight and help to ensure long-term sustainability. The main limitation of these tools lies in great computing demand when there is the necessity of solving large-scale tasks in great detail. It means that the ability to find the optimal solution for real-world problems is limited. Thus, the detail of infrastructure is often reduced by data aggregation or heuristic approaches are used to find a suboptimal solution. This paper proposes a machine learning classification model to reduce the number of variables for an exact solution algorithm. First, the design of experiments is used to create a set of smaller problems that are possible to solve exactly. Artificial data are used at this stage, while domain knowledge is used to set appropriate distribution and parameters. Second, the classification model estimates the probability of the presence of each arc in the optimal solution. Features, which are related to costs and capacity, of each arc are utilized in the classification model. Models created on a subset of generated problems are then tested on the other problems. Finally, the proposed framework is applied to the waste management problem in the Czech Republic. The results of the verification show, that it is possible to remove 95% of arcs without impact on strategic decisions and without significant change of an objective function. The computing time of the reduced problem takes only 7% of the original task.
Statistical static timing analysis via modern optimization lens: I. Histogram-based approach
Authors: Bosák Adam , Mishagli Dmytro , Mareček Jakub 
Published: September 2023

AbstractStatistical Static Timing Analysis (SSTA) is studied from the point of view of mathematical optimization. We present two formulations of the problem of finding the critical path delay distribution that were not known before: (i) a formulation of the SSTA problem using Binary–Integer Programming and (ii) a practical formulation using Geometric Programming. For simplicity, we use histogram approximation of the distributions. Scalability of the approaches is studied and possible generalizations are discussed.
A scientometric analysis of the effect of COVID-19 on the spread of research outputs
Authors: Zammarchi Gianpaolo , Carta Andrea , Columbu Silvia , Frigau Luca , Musio Monica 
Published: September 2023

AbstractThe spread of the COVID-19 pandemic in 2020 had a huge impact on the life course of all of us. This rapid spread has also caused an increase in the research production in topics related to different aspects of COVID-19. Italy has been one of the first countries to be massively involved in the outbreak of the disease. In this paper, we present an extensive scientometric analysis of the research production both at global (entire literature produced in the first 2 years after the beginning of the pandemic) and local level (COVID-19 literature produced by authors with an Italian affiliation). Our results showed that US and China are the most active countries in terms of number of publications and that the number of collaborations between institutions varies depending on geographical distance. Moreover, we identified the medical-biological as the field with the greatest growth in terms of literature production. As regards the analysis focused on Italy, we have shown that most of the collaborations follow a geographical pattern, both externally (with a preference for European countries) and internally (two clusters of institutions, north versus center-south). Furthermore, we explored the relationship between the number of citations and variables obtained from the data set (e.g. number of authors). Using multiple correspondence analysis and quantile regression we shed light on the role of journal topics and impact factor, the type of article, the field of study and how these elements affect citations.