bluuebunny/crossref_metadata_2025_split huggingface dataset:
Second-order electrogyration effect in BSO crystal
Authors: Guerrero-V María Alejandra , Rueda-P Jorge-Enrique 
Published: October 2024

AbstractUsing a non-holographic optical setup, we employed a Mueller–Stokes polarimeter to measure both the linear electro-optic and second-order electrogyration effects. The second-order electrogyration effect was observed in a $$Bi_{12}SiO_{20}$$

B

i
12

S
i

O
20

(BSO) crystal with a (110) cut. This response was found for the electric field applied both parallel and perpendicular to the [001] direction, where the values for the second-order electrogyration are $$4.86\times 10^{7} \, \text {pm}^{2}/\text {V}^{2}$$

4.86
×

10
7

pm
2

/

V
2

and $$1.87\times 10^{7} \, \text {pm}^{2}/\text {V}^{2}$$

1.87
×

10
7

pm
2

/

V
2

, respectively. Additionally, the linear electro-optic coefficient $$\gamma _{41}$$

γ
41

was measured to be $$1.17 \, \text {pm/V}$$

1.17

pm/V

for $$660.5 \, \text {nm}$$

660.5

nm

.
Optimizing risk stratification for intermediate-risk prostate cancer – the prognostic value of baseline health-related quality of life
Authors: Westhofen Thilo , Buchner Alexander , Lennartz Simon , Rodler Severin , Eismann Lennert , Aydogdu Can , Askari-Motlagh Darjusch , Berg Elena , Feyerabend Enya , Kazmierczak Philipp , Jokisch Friedrich , Becker Armin , Stief Christian G. , Kretschmer Alexander 
Published: October 2024

Abstract
Objective
To investigate the prognostic value of baseline health-related quality of life (HRQOL) for patients with intermediate-risk localized prostate cancer (IR-PCa) undergoing radical prostatectomy (RP).

Methods
4780 patients with IR-PCa according to NCCN risk stratification were identified from a prospectively maintained database. All patients were treated with RP and had prospectively assessed baseline HRQOL. Main outcomes were oncologic endpoints metastasis-free survival (MFS); biochemical recurrence free survival (BRFS) and overall survival (OS). Multivariable Cox regression models assessed prognostic significance of baseline global health status (GHS) on survival outcomes. Harrell’s discrimination C-index was applied to calculate the predictive accuracy of the model. Decision curve analysis (DCA) tested the clinical net benefit associated with adding the GHS domain to our multivariable model (p < 0.05).

Results
Median follow-up was 51 months. Multivariable analysis confirmed baseline GHS as an independent predictor for increased MFS (HR 0.976, 95%CI 0.96–0.99; p < 0.001), increased BRFS (HR 0.993, 95%CI 0.99–1.00; p = 0.027) and increased OS (HR 0.969, 95%CI 0.95–0.99; p = 0.002), indicating a relative risk reduction of 2.4% for MFS, 0.7% for BRFS and 3.1% for OS per 1-point increase of baseline GHS. Baseline HRQOL improved discrimination in predicting MFS, BRFS and OS. DCA revealed a net benefit over all threshold probabilities.

Conclusions
We found baseline HRQOL to substantially improve risk stratification for the heterogeneous cohort of IR-PCa. Baseline HRQOL accurately predicts increased MFS, BRFS and OS. Our findings therefore support the role of preoperative HRQOL as an adjunct to established prognosticators for IR-PCa, potentially facilitating guidance of therapy.
Chasing sleep physicians: ChatGPT-4o on the interpretation of polysomnographic results
Authors: Seifen Christopher , Huppertz Tilman , Gouveris Haralampos , Bahr-Hamm Katharina , Pordzik Johannes , Eckrich Jonas , Smith Harry , Kelsey Tom , Blaikie Andrew , Matthias Christoph , Kuhn Sebastian , Buhr Christoph Raphael 
Published: October 2024

Abstract
Background
From a healthcare professional's perspective, the use of ChatGPT (Open AI), a large language model (LLM), offers huge potential as a practical and economic digital assistant. However, ChatGPT has not yet been evaluated for the interpretation of polysomnographic results in patients with suspected obstructive sleep apnea (OSA).

Aims/objectives
To evaluate the agreement of polysomnographic result interpretation between ChatGPT-4o and a board-certified sleep physician and to shed light into the role of ChatGPT-4o in the field of medical decision-making in sleep medicine.

Material and methods
For this proof-of-concept study, 40 comprehensive patient profiles were designed, which represent a broad and typical spectrum of cases, ensuring a balanced distribution of demographics and clinical characteristics. After various prompts were tested, one prompt was used for initial diagnosis of OSA and a further for patients with positive airway pressure (PAP) therapy intolerance. Each polysomnographic result was independently evaluated by ChatGPT-4o and a board-certified sleep physician. Diagnosis and therapy suggestions were analyzed for agreement.

Results
ChatGPT-4o and the sleep physician showed 97% (29/30) concordance in the diagnosis of the simple cases. For the same cases the two assessment instances unveiled 100% (30/30) concordance regarding therapy suggestions. For cases with intolerance of treatment with positive airway pressure (PAP) ChatGPT-4o and the sleep physician revealed 70% (7/10) concordance in the diagnosis and 44% (22/50) concordance for therapy suggestions.

Conclusion and significance
Precise prompting improves the output of ChatGPT-4o and provides sleep physician-like polysomnographic result interpretation. Although ChatGPT shows some shortcomings in offering treatment advice, our results provide evidence for AI assisted automation and economization of polysomnographic interpretation by LLMs. Further research should explore data protection issues and demonstrate reproducibility with real patient data on a larger scale.
Attrition between lines of therapy and real-world outcomes of patients with HER2-positive metastatic breast cancer in Europe: a cohort study leveraging electronic medical records
Authors: Cottu Paul , Cheeseman Sue , Hall Peter , Wöckel Achim , Scholz Christian W. , Bria Emilio , Orlandi Armando , Ribelles Nuria , Vallet Mahéva , Niklas Nicolas , Hogg Catherine , Aggarwal Shivani , Moreira Joana , Lucerna Markus , Collin Simon M. , Logue Amanda , Long Gráinne H. 
Published: October 2024

Abstract

Purpose
To characterize real-world attrition rates across first-line (1L) to third-line (3L) therapies in patients with HER2-positive (HER2 +) metastatic breast cancer (mBC) receiving routine care in seven hospital systems across Europe (France, Germany, Italy, Spain, and the UK).

Methods
This retrospective, observational, multi-country, cohort study collected electronic medical record data from women aged ≥ 18 years diagnosed with HER2 + mBC from 2017–2021. The primary endpoint was attrition rate (the proportion of patients receiving a line of therapy [LOT] with no further evidence of subsequent LOTs). Key additional endpoints included treatment patterns, real-world time to treatment discontinuation (TTD), and time to next treatment (TTNT).

Results
29.6% (95% confidence interval [CI] 25.0–34.6) and 34.2% (95% CI 27.5–41.5) of treated patients with HER2 + mBC had no further evidence of treatment beyond 1L and second-line (2L) therapy, respectively. Attrition was primarily owing to death, move to end-of-life palliative care, loss to follow up, and “other” reasons. Treatment patterns were generally aligned with clinical guidelines. Decreases in TTD (12.1 months [95% CI 10.4–14.5] for 1L, 8.9 months [95% CI 7.3–11.9] for 2L, 6.4 months [95% CI 5.2–8.9] for 3L) and TTNT (15.4 months [95% CI 13.6–20.6] for 1L, 13.5 months [95% CI 10.8–19.4] for 2L) were observed with each subsequent LOT.

Conclusion
Results unveil a large proportion of patients who do not benefit from state-of-the-art subsequent LOT, and suggest diminishing effectiveness with each subsequent LOT.
Promoting Healthy Lifestyle Behaviours in Pre-Schoolers with the SuperFIT Take-Home Kit
Authors: Harms Lisa S. E. , Gubbels Jessica S. , Bessems Kathelijne M. H. H. , Penders Sid , Pluim Daan , Gerards Sanne M. P. L. 
Published: October 2024

AbstractInterventions targeting nutrition and physical activity levels of pre-schoolers through early childhood education and care (ECEC) increasingly aim to involve families and the home setting. How to optimise the reach and adoption of interventions by parents remains an important question. This study aimed to assess the feasibility and acceptability of a take-home kit to promote nutrition and physical activity (PA) of pre-schoolers at home, while exploring the participatory approach of its development, implementation and evaluation. Three successive versions of the take-home kit were developed and distributed among 21 ECEC centres and 199 families in South-Limburg, the Netherlands. Acceptability and feasibility of the kit were monitored and acted upon throughout the research period. The take-home kit included a stuffed toy, PA and nutrition cards with simple activities, a journal in which parents were asked to record their activities, and written instructions. One kit per ECEC centre rotated between families. Thirty-seven parents participated in open-ended questionnaires, and ECEC teachers from six centres and five implementers participated in interviews. Both questionnaires and interviews included questions about the acceptability (i.e. content, design), feasibility and self-reported impact of the take-home kit. Parents appreciated the tangible and practical aspects of the materials. Using children’s play experience and clear instructions from ECEC teachers facilitated implementation at home. Both implementers and ECEC teachers needed room for contextualised solutions to barriers to implementing the take-home kit in practice. Based on the present study, we conclude that take-home kits can be a valuable tool for ECEC to reach and support parents in adopting healthy energy balance-related behaviours at home.
Perspective: on the importance of extensive, high-quality and reliable deposition of biomolecular NMR data in the age of artificial intelligence
Authors: Higman Victoria A. , Płoskoń Eliza , Thompson Gary S. , Vuister Geerten W. 
Published: October 2024

AbstractArtificial intelligence (AI) models are revolutionising scientific data analysis but are reliant on large training data sets. While artificial training data can be used in the context of NMR processing and data analysis methods, relating NMR parameters back to protein sequence and structure requires experimental data. In this perspective we examine what the biological NMR community needs to do, in order to store and share its data better so that we can make effective use of AI methods to further our understanding of biological molecules. We argue, first, that the community should be depositing much more of its experimental data. In particular, we should be depositing more spectra and dynamics data. Second, the NMR data deposited needs to capture the full information content required to be able to use and validate it adequately. The NMR Exchange Format (NEF) was designed several years ago to do this. The widespread adoption of NEF combined with a new proposal for dynamics data specifications come at the right time for the community to expand its deposition of data. Third, we highlight the importance of expanding and safeguarding our experimental data repository, the Biological Magnetic Resonance Data Bank (BMRB), not only in the interests of NMR spectroscopists, but biological scientists more widely. With this article we invite others in the biological NMR community to champion increased (possibly mandatory) data deposition, to get involved in designing new NEF specifications, and to advocate on behalf of the BMRB within the wider scientific community.
Modelling and solving the university course timetabling problem with hybrid teaching considerations
Authors: Davison Matthew , Kheiri Ahmed , Zografos Konstantinos G. 
Published: October 2024

AbstractThe university course timetabling problem is a challenging problem to solve. As universities have evolved, the features of this problem have changed. One emerging feature is hybrid teaching where classes can be taught online, in-person or a combination of both in-person and online. This work presents a multi-objective binary programming model that includes common university timetabling features, identified from the literature, as well as hybrid teaching features. A lexicographic solution method is outlined and computational experiments using benchmark data are used to demonstrate the key aspects of the model and explore trade-offs among the objectives considered. The results of these experiments demonstrate that the model can be used to find demand-driven schedules for universities that include hybrid teaching. They also show how the model could be used to inform practitioners who are involved in strategic decision-making at universities.
Interweaving Insights: High-Order Feature Interaction for Fine-Grained Visual Recognition
Authors: Sikdar Arindam , Liu Yonghuai , Kedarisetty Siddhardha , Zhao Yitian , Ahmed Amr , Behera Ardhendu 
Published: October 2024

AbstractThis paper presents a novel approach for Fine-Grained Visual Classification (FGVC) by exploring Graph Neural Networks (GNNs) to facilitate high-order feature interactions, with a specific focus on constructing both inter- and intra-region graphs. Unlike previous FGVC techniques that often isolate global and local features, our method combines both features seamlessly during learning via graphs. Inter-region graphs capture long-range dependencies to recognize global patterns, while intra-region graphs delve into finer details within specific regions of an object by exploring high-dimensional convolutional features. A key innovation is the use of shared GNNs with an attention mechanism coupled with the Approximate Personalized Propagation of Neural Predictions (APPNP) message-passing algorithm, enhancing information propagation efficiency for better discriminability and simplifying the model architecture for computational efficiency. Additionally, the introduction of residual connections improves performance and training stability. Comprehensive experiments showcase state-of-the-art results on benchmark FGVC datasets, affirming the efficacy of our approach. This work underscores the potential of GNN in modeling high-level feature interactions, distinguishing it from previous FGVC methods that typically focus on singular aspects of feature representation. Our source code is available at https://github.com/Arindam-1991/I2-HOFI.
Simulation of Somatic Evolution Through the Introduction of Random Mutation to the Rules of Conway’s Game of Life
Authors: King Michael R. 
Published: October 2024

Abstract

Introduction
Conway’s Game of Life (GOL), and related cellular automata (CA) models, have served as interesting simulations of complex behaviors resulting from simple rules of interactions between neighboring cells, that sometime resemble the growth and reproduction of living things. Thus, CA has been applied towards understanding the interaction and reproduction of single-cell organisms, and the growth of larger, disorganized tissues such as tumors. Surprisingly, however, there have been few attempts to adapt simple CA models to recreate the evolution of either new species, or subclones within a multicellular, tumor-like tissue.

Methods
In this article, I present a modified form of the classic Conway’s GOL simulation, in which the three integer thresholds that define GOL (number of neighboring cells, below which a cell will “die of loneliness”; number of neighboring cells, above which a cell will die of overcrowding; and number of neighboring cells that will result in spontaneous birth of a new cell within an empty lattice location) are occasionally altered with a randomized mutation of fractional magnitude during new “cell birth” events. Newly born cells “inherit” the current mutation state of a neighboring parent cell, and over the course of 10,000 generations these mutations tend to accumulate until they impact the behaviors of individual cells, causing them to transition from the sparse, small patterns of live cells characteristic of GOL into a more dense, unregulated growth resembling a connected tumor tissue.

Results
The mutation rate and mutation magnitude were systematically varied in repeated randomized simulation runs, and it was determined that the most important mutated rule for the transition to unregulated, tumor-like growth was the overcrowding threshold, with the spontaneous birth and loneliness thresholds being of secondary importance. Spatial maps of the different “subclones” of cells that spontaneously develop during a typical simulation trial reveal that cells with greater fitness will overgrow the lattice and proliferate while the less fit, “wildtype” GOL cells die out and are replaced with mutant cells.

Conclusions
This simple modeling approach can be easily modified to add complexity and more realistic biological details, and may yield new understanding of cancer and somatic evolution.
ChatGPT versus human essayists: an exploration of the impact of artificial intelligence for authorship and academic integrity in the humanities
Authors: Revell T. , Yeadon W. , Cahilly-Bretzin G. , Clarke I. , Manning G. , Jones J. , Mulley C. , Pascual R. J. , Bradley N. , Thomas D. , Leneghan F. 
Published: October 2024

AbstractGenerative AI has prompted educators to reevaluate traditional teaching and assessment methods. This study examines AI’s ability to write essays analysing Old English poetry; human markers assessed and attempted to distinguish them from authentic analyses of poetry by first-year undergraduate students in English at the University of Oxford. Using the standard UK University grading system, AI-written essays averaged a score of 60.46, whilst human essays achieved 63.57, a margin of difference not statistically significant (p = 0.10). Notably, student submissions applied a nuanced understanding of cultural context and secondary criticism to their close reading, while AI essays often described rather than analysed, lacking depth in the evaluation of poetic features, and sometimes failing to properly recognise key aspects of passages. Distinguishing features of human essays included detailed and sustained analysis of poetic style, as well as spelling errors and lack of structural cohesion. AI essays, on the other hand, exhibited a more formal structure and tone but sometimes fell short in incisive critique of poetic form and effect. Human markers correctly identified the origin of essays 79.41% of the time. Additionally, we compare three purported AI detectors, finding that the best, ‘Quillbot’, correctly identified the origin of essays 95.59% of the time. However, given the high threshold for academic misconduct, conclusively determining origin remains challenging. The research also highlights the potential benefits of generative AI’s ability to advise on structuring essays and suggesting avenues for research. We advocate for transparency regarding AI’s capabilities and limitations, and this study underscores the importance of human critical engagement in teaching and learning in Higher Education. As AI’s proficiency grows, educators must reevaluate what authentic assessment is, and consider implementing dynamic, holistic methods to ensure academic integrity.
Enhancing sustainability in agriculture with nanofertilizers
Authors: Saurabh Kirti , Prakash Ved , Dubey Abhishek Kumar , Ghosh Sonaka , Kumari Arti , Sundaram Prem K. , Jeet Pawan , Sarkar Bikash , Upadhyaya Ashutosh , Das Anup , Kumar Santosh , Makarana Govind , Kumar Ujjwal , Kumar Atish , Singh Ravi Ranjan 
Published: October 2024

AbstractThe pursuit of sustainable agriculture has become imperative in addressing global food security challenges while minimizing environmental impacts. Recent innovations in nanotechnology have given rise to a promising solution: nanofertilizers. Research reveals that these nanofertilizers can significantly enhance nutrient use efficiency, reducing environmental consequences, and advancing the cause of cleaner production. With potential increases of up to 30% in nutrient use efficiency and 20% in crop yields compared to traditional fertilizers, nanofertilizers demonstrate the capability to substitute up to 50% of conventional fertilizers, thereby diminishing their ecological footprint. This review paper explores the emerging trends and advancements in the field of nanofertilizers and their potential to revolutionize modern agriculture. We delve into the fundamental concepts of nanofertilizers, including their unique characteristics and controlled-release mechanisms. We analysed the impact of nanofertilizers on crop productivity, quality, and growth through the lens of research findings and case studies. While acknowledging the substantial potential of nanofertilizers, we also address environmental and safety considerations, emphasizing the importance of responsible deployment. In an era prioritizing environmental concerns, nanofertilizers offer a promising solution to meet growing food demands while protecting ecosystems.
Graphical Abstract
Young people’s participation in urban landscape planning and transformation: a scoping review of interactive approaches
Authors: Hagemann Frederik Aagaard , Sang Åsa Ode , Randrup Thomas Barfoed 
Published: October 2024

AbstractThis article presents a review of methodological advancements and transformative potential in participatory processes with young people in urban landscapes. It offers a framework understanding of current types of participatory processes in relation to urban landscape planning, and underlines lifeworld and action as two key components in transformative participatory processes with young people. The two-step scoping review of a literature sample (n = 44 studies) finds a prevalence of less-interactive approaches to young people’s participation in urban landscapes, and subsequently analyses openings for lifeworld and action in the more interactive approaches described (n = 17 studies). The interactive methods described demonstrate opportunities to facilitate young people’s own articulations of lifeworlds within the urban landscape, especially in extended processes deploying multiple creative methods. The relatively few examples of actions and interventions resulting from participatory processes points to the need for further development and the ambition to include young people in transforming urban landscapes towards increased sustainability.
Expanding Pharmaceutical Access Via Over the Counter Drugs
Authors: Jouaneh Terra Marie M. , Gowda Vrushab , Miller Brian J. 
Published: October 2024

AbstractThis commentary addresses the recent U.S. Food & Drug Administration (FDA) proposed rule to expand access to nonprescription drugs through additional conditions of nonprescription use (ACNU). It surveys the various pathways to market for pharmaceutical products, noting the distinct requirements for over-the-counter (OTC) products differentiating them from prescription products. It subsequently reviews the ACNU proposed rule, weighing its potential benefits against possible limitations. With a view towards the future, the ACNU proposed rule is acknowledged as part of a longstanding tradition to expand drug channels in a risk-stratified fashion with increasing clinical oversight to address in tandem increasing consumer risks. Finally, the proposed rule also serves as a potential prelude for a future behind the counter drug pathway.