bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association of hospital volume with survival but not with postoperative mortality in glioblastoma patients in Belgium
Authors: Vanhauwaert Dimitri , Silversmit Geert , Vanschoenbeek Katrijn , Coucke Gregory , Di Perri Dario , Clement Paul M. , Sciot Raf , De Vleeschouwer Steven , Boterberg Tom , De Gendt Cindy 
Published: August 2024

Abstract
Objectives
Standard of care treatment for glioblastoma (GBM) involves surgical resection followed by chemoradiotherapy. However, variations in treatment decisions and outcomes exist across hospitals and physicians. In Belgium, where oncological care is dispersed, the impact of hospital volume on GBM outcomes remains unexplored. This nationwide study aims to analyse interhospital variability in 30-day postoperative mortality and 1-/2-year survival for GBM patients.

Methods
Data collected from the Belgian Cancer Registry, identified GBM patients diagnosed between 2016 and 2019. Surgical resection and biopsy cases were identified, and hospital case load was determined. Associations between hospital volume and mortality and survival probabilities were analysed, considering patient characteristics. Statistical analysis included logistic regression for mortality and Cox proportional hazard models for survival.

Results
A total of 2269 GBM patients were identified (1665 underwent resection, 662 underwent only biopsy). Thirty-day mortality rates post-resection/post-biopsy were 5.1%/11.9% (target < 3%/<5%). Rates were higher in elderly patients and those with worse WHO-performance scores. No significant difference was found based on hospital case load. Survival probabilities at 1/2 years were 48.6% and 21.3% post-resection; 22.4% and 8.3% post-biopsy. Hazard ratio for all-cause death for low vs. high volume centres was 1.618 in first 0.7 year post-resection (p < 0.0001) and 1.411 in first 0.8 year post-biopsy (p = 0.0046).

Conclusion
While 30-day postoperative mortality rates were above predefined targets, no association between hospital volume and mortality was found. However, survival probabilities demonstrated benefits from treatment in higher volume centres, particularly in the initial months post-surgery. These variations highlight the need for continuous improvement in neuro-oncological practice and should stimulate reflection on the neuro-oncological care organisation in Belgium.
Construction of a Farm-Level Food Security Index: Case Study of Turkish Dairy Farms
Authors: Koç Gökçe , Uzmay Ayşe 
Published: August 2024

AbstractFood security continues to be a global concern and its importance has recently increased for many reasons. Composite food security indices have been widely used to calculate and monitor food security, but farm-level studies are limited. Therefore, the main objective of this study is to construct a Farm-level Food Security Index (FFSI) for dairy farms to assess their contribution to food security, identify potential areas for improvement and guide policy makers. Data were collected from 126 farms in the Thrace Region of Turkey through face-to-face interviews. The FFSI was constructed with four dimensions, briefly called economic, quality, social and natural resources, containing twenty-three variables. Principal component analysis was used for the determination of variable weights, data envelopment analysis for calculating technical efficiency, and the Tobit model for examining the factors influencing FFSI scores. To assess the robustness of the FFSI, Monte Carlo simulations-based uncertainty and sensitivity analysis, dimension extraction approach and Shapley effects sensitivity analysis were performed. With an average score of 56.8, the key result of the FFSI is that dairy farms are using almost half of their potential to fully contribute to food security. Moreover, according to the Tobit model, FFSI scores are significantly affected by the farmer’s age and education level, credit use, livestock unit, fodder crop area and milk marketing channel. The FFSI is robust to weights and sensitive to normalisation, and the social sustainability dimension can cause the largest shift in index scores. Based on these findings, numerous agricultural policy proposals have been developed in this study by identifying the priority areas that need to be addressed to guarantee food security.
Intentional action, knowledge, and cognitive extension
Authors: Carter J. Adam , Andrada Gloria 
Published: August 2024

AbstractIntentional actions exhibit control in a way that mere lucky successes do not. A longstanding tradition in action theory characterizes actional control in terms of the knowledge with which one acts when acting intentionally. Given that action theorists, no less than epistemologists, typically take for granted the orthodox thesis that knowledge is in the head (viz., realized exclusively by brainbound cognition), the idea that intentional action is controlled in virtue of knowledge is tantamount to the idea that the knowledge by which intentional actions exhibit control supervenes intracranially. We raise some challenges for this idea, and in doing show, we show how epistemic theories of actional control are naturally aligned moreso than has been appreciated with cognitive extension in the theory of mind.
Ionic Liquids as Extreme Pressure Additives for Bearing Steel Applications
Authors: Donato Mariana T. , Nautiyal Pranjal , Deuermeier Jonas , Branco Luís C. , Saramago Benilde , Colaço Rogério , Carpick Robert W. 
Published: August 2024

AbstractThe protection of steel surfaces from wear under extreme pressure conditions is of major importance in several industries as it provides better performance and longer life of machinery. The motivation for this work was to study the lubrication of steel by ionic liquids (ILs), which have recently emerged as greener alternatives to commercial lubricants and additives. Three ILs based on sulfur-containing anions, used as 2-wt% additives in polyethylene glycol base oil (MW 200; PEG 200), were tested in the lubrication of ASTM 52100 bearing steel contacts in extreme pressure conditions (under mixed lubrication with a Hertzian pressure of 1.12 GPa) using a mini traction machine (MTM). Due to the poor resistance to corrosion of bearing steel, a semi-ester of succinic acid derivative corrosion inhibitor (Lanxess RC 4801) was added to the mixtures at a 1 wt% concentration. The ILs 1-hexyl-methylimidazolium trifluoromethanesulfonate ([C6mim][TfO]) and 1-hexyl-4-picolinium trifluoromethanesulfonate ([C6-4-pic][TfO]) revealed promising results in terms of surface protection of bearing steel. In contrast, 4-picolinium hydrogen sulfate ([4-picH][HSO4]) as 2-wt% additive to PEG 200 + 1% RC 4801 did not show any improvement in wear performance compared to neat PEG 200 + 1% RC 4801. PEG 200 + 2% [C6mim][TfO] + 1%RC 4801 allowed for a decrease in wear up to ~ 76% and PEG 200 + 2% [C6-4-pic][TfO] + 1%RC 4801 up to ~ 46% when compared with neat PEG 200 + 1% RC 4801. Optical microscopy images suggest the formation of an adsorbed layer, which was further supported by chemical analysis via x-ray photoelectron spectroscopy (XPS) data for [C6mim][TfO].
Graphical abstract
Search for natural products from actinomycetes of the genus Nocardia
Authors: Hara Yasumasa 
Published: August 2024

AbstractThe genus Nocardia are gram-positive bacteria, many of which possess pathogenicity and infect human lungs, skin, brain, and other organs. Since research on the genus Nocardia has not progressed as rapidly as that on the genus Streptomyces, the genus Nocardia is considered a useful undeveloped resource for exploring natural products. On the other hand, when the genus Nocardia infects the human body, the strains are attacked by immune cells such as macrophages. Therefore, we suggested a new method for screening natural products by culturing the genus Nocardia in the presence of animal cells. In this review, we describe our recent results in searching for natural products from the genus Nocardia.
Graphical abstract
A proposed methodology for investigating student-chatbot interaction patterns in giving peer feedback
Authors: Lin Michael Pin-Chuan , Chang Daniel H. , Winne Philip H. 
Published: August 2024

AbstractA chatbot is artificial intelligence software that converses with a user in natural language. It can be instrumental in mitigating teaching workloads by coaching or answering student inquiries. To understand student-chatbot interactions, this study is engineered to optimize student learning experience and instructional design. In this study, we developed a chatbot that supplemented disciplinary writing instructions to enhance peer reviewer’s feedback on draft essays. With 23 participants from a lower-division post-secondary education course, we delved into characteristics of student-chatbot interactions. Our analysis revealed students were often overconfident about their learning and comprehension. Drawing on these findings, we propose a new methodology to identify where improvements can be made in conversation patterns in educational chatbots. These guidelines include analyzing interaction pattern logs to progressively redesign chatbot scripts that improve discussions and optimize learning. We describe new methodology providing valuable insights for designing more effective instructional chatbots by enhancing and engaging student learning experiences through improved peer feedback.
Duale und schulische Berufsausbildungen in Deutschland: Schritte zu einem umfassenden Verständnis von beruflicher Bildung
Authors: Weitz Jennifer , Ludwig-Mayerhofer Wolfgang 
Published: August 2024

ZusammenfassungDie berufliche Ausbildung in Deutschland wird auch heute noch häufig mit der dualen Ausbildung gleichgesetzt. Schulische Berufsausbildungen können im doppelten Sinn als Ausbildungen zweiter Klasse gesehen werden: Sie werden in Öffentlichkeit und Wissenschaft seltener wahrgenommen; geraten sie aber in den Blick, so wird oftmals angenommen, dass die (überwiegend weiblichen) Personen, die solche Ausbildungen absolvieren, im Vergleich zu dual Ausgebildeten schlechtere Arbeitsmarktchancen haben. Der Beitrag skizziert zunächst duale Ausbildungen, Ausbildungen an Schulen des Gesundheitswesens sowie Ausbildungen an Berufsfachschulen (unter gesonderter Betrachtung der Erzieher:innen) im gesellschaftlich-historischen Kontext und zeigt, wie dieser Kontext letztlich auch mit unzureichender Forschung zu den schulischen Ausbildungen einhergeht. Mit Daten des Nationalen Bildungspanels (NEPS) werden anschließend die Chancen von Absolvent:innen der verschiedenen Ausbildungssegmente beim Übergang in den Arbeitsmarkt analysiert (Dauer bis zur ersten Beschäftigung, Merkmale des ersten Beschäftigungsverhältnisses sowie Arbeitslosigkeit nach der ersten Beschäftigung). Im Ergebnis zeigt sich, dass die (nicht bundesweit, sondern per Ländergesetzgebung geregelten) Ausbildungen an Berufsfachschulen tatsächlich mit etwas schlechteren Arbeitsmarktchancen verknüpft sind. Auffällig ist das Profil der Erzieher:innen, die besonders häufig befristet beschäftigt sind. Mit Blick auf den Beschäftigungsbedarf der Zukunft sind mehr öffentliche Aufmerksamkeit und mehr staatliches Engagement für die schulische Berufsbildung dringend erforderlich.
Designing for collective action: a knowledge co-production process to address water governance challenges on the island of Öland, Sweden
Authors: Seiferth Carolin , Tengö Maria , Andersson Erik 
Published: August 2024

AbstractEnabling diverse actors to address interlinked sustainability issues is important and challenging. This paper focuses on how to design a dialogue-based knowledge co-production process to nurture collective action. Using the conceptualization of systems, target, and operational knowledge as the guiding framework, we designed and combined different complementary activities to invite actors to look at a wicked problem through multiple lenses and reflect on their own positions, perspectives, knowledge, and values. With a carefully documented workshop series held with local actors on Öland, Sweden, as our empirical case study, we demonstrate how we moved from exploring the multifunctionality of landscapes and understanding actors’ different values, preferences, and priorities, to developing four strategies for effectively accelerating and expanding efforts to adapt to climate change. Our study reveals how the process of mobilizing, articulating, and connecting individually held systems, target, and operational knowledge nurtures collective action. It also leverages dialogue-based processes as cornerstones in addressing sustainability challenges in an inclusive and equitable way.
Importance of the (Pro)renin Receptor in Activating the Renin-Angiotensin System During Normotensive and Preeclamptic Pregnancies
Authors: Schofield Lachlan G. , Endacott Saije K. , Delforce Sarah J. , Lumbers Eugenie R. , Pringle Kirsty G. 
Published: August 2024

Abstract
Purpose of Review
For a healthy pregnancy to occur, a controlled interplay between the maternal circulating renin–angiotensin–aldosterone system (RAAS), placental renin-angiotensin system (RAS) and intrarenal renin-angiotensin system (iRAS) is necessary. Functionally, both the RAAS and iRAS interact to maintain blood pressure and cardiac output, as well as fluid and electrolyte balance. The placental RAS is important for placental development while also influencing the maternal circulating RAAS and iRAS. This narrative review concentrates on the (pro)renin receptor ((P)RR) and its soluble form (s(P)RR) in the context of the hypertensive pregnancy pathology, preeclampsia.

Recent Findings
The (P)RR and the s(P)RR have become of particular interest as not only can they activate prorenin and renin, thus influencing levels of angiotensin II (Ang II), but s(P)RR has now been shown to directly interact with and stimulate the Angiotensin II type 1 receptor (AT1R). Levels of both placental (P)RR and maternal circulating s(P)RR are elevated in patients with preeclampsia. Furthermore, s(P)RR has been shown to increase blood pressure in non-pregnant and pregnant rats and mice.

Summary
In preeclamptic pregnancies, which are characterised by maternal hypertension and impaired placental development and function, we propose that there is enhanced secretion of s(P)RR from the placenta into the maternal circulation. Due to its ability to both activate prorenin and act as an AT1R agonist, excess maternal circulating s(P)RR can act on both the maternal vasculature, and the kidney, leading to RAS over-activation. This results in dysregulation of the maternal circulating RAAS and overactivation of the iRAS, contributing to maternal hypertension, renal damage, and secondary changes to neurohumoral regulation of fluid and electrolyte balance, ultimately contributing to the pathophysiology of preeclampsia.
Infrared Thermal Image Processing Technique for Evaluating Superheated Steam as a Dry Sanitation Method
Authors: Park Hyeon Woo , Balasubramaniam V. M. 
Published: August 2024

Abstract
The objectives of this study were to develop a thermal image analysis method for assessing the surface temperature of stainless steel (30 cm × 30 cm) during pilot-scale superheated steam sanitation and evaluate the sanitation efficacy based on the inactivation of Enterococcus faecium. An infrared camera, calibrated to a root-mean-square error (RMSE) of 1.4 °C within a range of 25 °C and 250 °C, was utilized. The results showed that the surface temperature at the impingement point decreased linearly from 245.6 ± 3.2 to 157.6 ± 1.7 °C as the nozzle-to-surface distance was increased from 2 to 5 cm. Furthermore, at a 2 cm nozzle-to-surface distance, temperatures swiftly dropped from 245.6 ± 3.2 to 95.8 ± 6.0 °C as the radial distance increased from 0 to 10 cm. In the stagnation region (0–1 cm radial distance), where the steam jet directly contacts the surface, the time required to achieve a 3-log reduction of E. faecium was reduced from 3 to 1 min as the nozzle-to-surface distance decreased from 5 to 2 cm. The efficacy of superheated steam sanitation was further evaluated under practical sweeping conditions, demonstrating a 2.7 ± 0.4 log reduction of E. faecium on a 900 cm2 stainless steel surface within 10 min. This study thus highlights the potential use of thermal image analysis for optimizing superheated steam sanitation processes, particularly in dry food processing environments.
Dynamics of Freedom: Negotiating Constraints
Authors: Hejlesen Jonas Tellefsen 
Published: August 2024

AbstractIn this paper, I grapple with the question of why we, at times, experience ourselves as not free. In doing so I outline a crude theory of agency (and our experience of ourselves as free) as a dynamic process happening in irreversible time. In attempting to answer this question, I define agency as the ability to pursue our desires, and I claim that we experience ourselves as free as long as we can do this – with the caveat that the ability to reason is a necessary criterion. I show that agency is a sociocultural development that manifests as the ability to reason gradually develops through social interaction during infancy and into adulthood. Crucially, I point out that reason is a double-edged sword: It allows us to question our actions and desires and whether they are worth pursuing, which is what elevates us to agentic beings. However, it also allows us to alienate ourselves from our actions and desires, and thus rob ourselves of our experience of freedom. Lastly, I show how our subjective freedom is lost and gained in a constant process, generated by a reflexive-relating-to ourselves. As we act, we continually encounter constraints (physical and psychological) that bar us from acting upon our desires. This compels us to reflect on our actions and desires, and so, our feeling of freedom evaporates. However, through a retrospective forgetting, or reconstruction, of the constraints we encounter, we may regain our experience of being free.
Nonassociative cyclic algebras and the semiassociative Brauer monoid
Authors: Pumplün S. 
Published: August 2024

AbstractWe look at classes of semiassociative algebras, with an emphasis on those that canonically generalize associative (generalized) cyclic algebras, and at their behaviour in the semiassociative Brauer monoid defined by Blachar, Haile, Matzri, Rein, and Vishne. A possible way to generalize this monoid in characteristic p that includes nonassociative differential algebras is briefly considered.
A memetic algorithm for improved joint route selection and split-level management in next-generation wireless communications
Authors: Garza-Fabre Mario , Erazo-Agredo Cristian C. , Rubio-Loyola Javier 
Published: August 2024

AbstractThe complexity of next-generation wireless communications, especially Beyond 5G and 6G communication systems, will be handled by artificial intelligence-based management paradigms. The joint selection of routes and functional split levels involves critical decisions that network infrastructure providers need to make to support requests from virtual Mobile Network Operators (vMNOs). These decisions comprise the assignment and configuration of physical network resources, which must comply with the specific quality of service restrictions of each vMNO request. Recent work defined a detailed mathematical model for this complex challenge, its formulation as a constrained, discrete optimization problem, and the first algorithmic approaches. It was also found that an evolutionary algorithm delivers higher-quality solutions than an ad-hoc heuristic, and faster running times compared to a well-known commercial solver. This paper introduces a memetic algorithm that exploits the strengths of the former evolutionary method while incorporating several key innovations: a domain-specific recombination operator; a specialized repairing procedure; an enhanced fitness evaluation scheme; and a multiobjective archiving strategy that preserves promising solution trade-offs. We conduct a comprehensive evaluation of the performance and behavior of this proposal, as well as the contribution of each specific design component. The results highlight that our memetic algorithm consistently outperforms previous approaches from the literature, providing better trade-offs in terms of solution quality and the rate at which vMNO requests are successfully fulfilled.
When is blockchain worth it? Value and risk drivers of corporate blockchain announcements
Authors: Rogalski Timo , Schiereck Dirk 
Published: August 2024

AbstractIn the era of emerging technologies, many firms explore the role of blockchain technology and its impact on corporate market value. Past research has shown that companies benefit from executing blockchain projects, but little is known about specific value and risk drivers. Hence, we provide evidence for several conditions under which blockchain provides additional firm market value. Moreover, we test whether blockchain announcements lead to changes in the systematic risk of firms. Theoretically founded on the resource-based view, we utilize the event study methodology, supplemented by a multivariate regression and a firm’s beta analysis. We find that stock markets react positively to corporate blockchain news if the announcement is related to a blockchain consortium or partnership, is declared by a tech company, or if the announcement is a follow-up announcement to initial blockchain news. Moreover, our findings show that blockchain announcements do not lead to significant changes in a firm’s systematic risk.
Machine Learning as a Tool to Find New Pharmacological Targets in Mood Disorders: A Systematic Review
Authors: Romão Joana , Melo António , André Rita , Novais Filipa 
Published: August 2024

Abstract
Purpose of Review
Mood disorders (MD) are mental disorders that need accurate diagnosis and proper treatment. Growing volume of data from neurobehavioral sciences is becoming complex for traditional research to analyze. New drugs’ slow development fails to meet the needs of neurobehavioral disorders. Machine Learning (ML) techniques support research by refining the detection, diagnosis, treatment, and research, and are being employed to expedite the discovery of pharmacological targets. This review aims to assess evidence regarding the contribution of ML in finding new pharmacological targets in adults with MD.

Recent findings
The most significant area of research amongst MD is major depressive disorder. ML identified target gene candidates, pathways and biomarkers related to MD, which can pave the way for promising therapeutic strategies. ML was also found to enhance diagnostic accuracy.

Summary
ML techniques have the potential to bridge the gap between biological data and chemical drug information, providing new discoveries in pharmacological agents.
Utilizing Medical Student Feedback to Improve Teaching Cases in Pre-clerkship Curricula
Authors: Bruner Lia Pierson , Topper Leah , Baldwin Amy , House Ellen M. , Chappell M. Tresa , Hill Janette R. 
Published: August 2024

AbstractFeedback is an essential part of continuous quality improvement of cases used in medical curricula. This report describes results of qualitative analysis of feedback to elucidate what worked well and what needed improvement from the lens of our pre-clerkship medical students. Complexity, realism, and use of media were themes identified as strengths. Increasing the complexity, realism, and media as well as clarifying test results were themes for suggested improvements. While some feedback themes were similar across pre-clerkship years, others differed between first- and second-year students, likely representing the evolution of our learners.