bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning in the prediction and detection of new-onset atrial fibrillation in ICU: a systematic review
Authors: Glaser Krzysztof , Marino Luca , Stubnya Janos Domonkos , Bilotta Federico 
Published: April 2024

AbstractAtrial fibrillation (AF) stands as the predominant arrhythmia observed in ICU patients. Nevertheless, the absence of a swift and precise method for prediction and detection poses a challenge. This study aims to provide a comprehensive literature review on the application of machine learning (ML) algorithms for predicting and detecting new-onset atrial fibrillation (NOAF) in ICU-treated patients. Following the PRISMA recommendations, this systematic review outlines ML models employed in the prediction and detection of NOAF in ICU patients and compares the ML-based approach with clinical-based methods. Inclusion criteria comprised randomized controlled trials (RCTs), observational studies, cohort studies, and case–control studies. A total of five articles published between November 2020 and April 2023 were identified and reviewed to extract the algorithms and performance metrics. Reviewed studies sourced 108,724 ICU admission records form databases, e.g., MIMIC. Eight prediction and detection methods were examined. Notably, CatBoost exhibited superior performance in NOAF prediction, while the support vector machine excelled in NOAF detection. Machine learning algorithms emerge as promising tools for predicting and detecting NOAF in ICU patients. The incorporation of these algorithms in clinical practice has the potential to enhance decision-making and the overall management of NOAF in ICU settings.
Multi-battle contests over complementary battlefields
Authors: Stephenson Daniel 
Published: April 2024

AbstractThis paper studies contests with complementary prizes where each agent simultaneously distributes a fixed budget over multiple battlefields. Each battlefield has a single prize which is divided among the competitors in proportion to an arbitrary power function of their investment levels. A unique pure strategy Nash equilibrium is shown to exist under arbitrarily sensitive battlefield success functions if objective functions exhibit constant subunitary elasticity of substitution between prize shares. In contrast, Blotto contests with linear objectives have only mixed strategy Nash equilibria if battlefield success functions are sufficiently sensitive to investment levels. Sufficient complementarity between prize shares allows pure strategy Nash equilibria to exist under arbitrarily sensitive battlefield success functions.
Optimized trans-cranial direct current stimulation for prolonged consciousness disorder in a patient with titanium mesh cranioplasty
Authors: Im Sun , Park Geun-Young , Kim Tae-Woo , Lim Seong Hoon 
Published: April 2024

Abstract
Background
Transcranial direct current stimulation (tDCS) has been used for the restoration of awareness in patients with a minimal consciousness state (MCS). Most brains of patients in MCS may structurally and electrophysiologically differ from un-damaged brains. Moreover, tDCS is currently contraindicated for patients with craniotomy or skull with metallic implants.

Case Presentation
We present a case with prolonged MCS over 1 year, who had severe brain damage, ventriculoperitoneal shunt, and cranioplasty with a titanium mesh, which was treated with tDCS which optimized with the simulation of the electric field based on the patient’s brain MRI. The patient was resulting in emergence from MCS. Six months later, she ate meals orally and started walking with assistance.

Discussion and perspective
This personalized simulation based on MRI would make the treatment available even to patients with severe brain structural changes and metallic instrumentation.
Evaluation of school-based interventions including homework to promote healthy lifestyles: a systematic review with meta-analysis
Authors: Masini Alice , Salussolia Aurelia , Anastasia Alessandra , Grao-Cruces Alberto , Soldà Giorgia , Zanutto Giorgia , Riegger Stephan , Mulato Raffaela , Sánchez-Oliva David , Ceciliani Andrea , Marini Sofia , Dallolio Laura 
Published: April 2024

Abstract
Aim
It is important to promote healthy lifestyles in youth through initiatives in school, which is a preferred setting to implement health-related interventions also targeted at families to be more effective. This study aimed to synthesise school-based interventions including homework and extracurricular activities for the promotion of healthy lifestyles, especially healthy nutrition and physical activity, in children and adolescents.

Methods
This systematic review was conducted according to the PRISMA guidelines. Quality assessment was performed using the Cochrane Tool for Quality Assessment for randomized and non-randomized control trials, while the STROBE (Strengthening the Reporting of Observational studies in Epidemiology) guidelines were used for observational studies.

Results
From the 1356 studies identified, eight were included. Across studies, a significant effect was found in increasing fruit and vegetable consumption and reducing snack and sugar intake, while no effect was found for moderate to vigorous physical activity (MVPA) unless for light PA (LPA) and step counts. The results of BMI and waist circumference are still unclear after performing a meta-analysis of three studies.

Conclusion
School-based interventions including homework and extracurricular activities were shown to improve nutritional behaviour, step counts, and LPA. Despite some statistically significant results, the effects of BMI and waist circumference are still unclear. Further studies are needed to demonstrate that these intervention s can represent an effective strategy for obesity prevention.
Automated sample preparation for electrospray ionization mass spectrometry based on CLOCK-controlled autonomous centrifugal microfluidics
Authors: Futami Masahiro , Naito Hiroki , Ninomiya Satoshi , Chen Lee Chuin , Iwano Tomohiko , Yoshimura Kentaro , Ukita Yoshiaki 
Published: April 2024

AbstractWe report a centrifugal microfluidic device that automatically performs sample preparation under steady-state rotation for clinical applications using mass spectrometry. The autonomous microfluidic device was designed for the control of liquid operation on centrifugal hydrokinetics (CLOCK) paradigm. The reported device was highly stable, with less than 7% variation with respect to the time of each unit operation (sample extraction, mixing, and supernatant extraction) in the preparation process. An agitation mechanism with bubbling was used to mix the sample and organic solvent in this device. We confirmed that the device effectively removed the protein aggregates from the sample, and the performance was comparable to those of conventional manual sample preparation procedures that use high-speed centrifugation. In addition, probe electrospray ionization mass spectrometry (PESI-MS) was performed to compare the device-treated and manually treated samples. The obtained PESI-MS spectra were analyzed by partial least squares discriminant analysis, and the preparation capability of the device was found to be equivalent to that of the conventional method.
Recreational physical activity and breast cancer risk by menopausal status and tumor hormone receptor status: results from the Nurses’ Health Studies
Authors: Fortner Renée T. , Brantley Kristen D. , Tworoger Shelley S. , Tamimi Rulla M. , Rosner Bernard , Holmes Michelle D. , Willett Walter C. , Eliassen A. Heather 
Published: April 2024

Abstract
Purpose
Physical activity is associated with lower breast cancer risk, especially in postmenopausal women. Associations in premenopausal women are less well established.

Methods
We evaluated recreational physical activity and breast cancer risk in the Nurses’ Health Study (NHS) and NHSII (187,278 women; n = 12,785 breast cancers; follow-up: NHS = 1986–2016, NHSII = 1989–2017) by menopausal status and estrogen (ER) and progesterone (PR) receptor status. Physical activity was evaluated as updated cumulative average of metabolic equivalent of task (MET)-h/week. Cox proportional hazards models were used to estimate multivariable hazard ratios (HR) and 95% confidence intervals (CI).

Results
Recreational physical activity was inversely associated with breast cancer risk in pre- and postmenopausal women. Higher activity levels were associated with lower risk of ER+/PR + breast cancer in both pre- and postmenopausal women (e.g., total recreational activity, ≥ 27 vs < 3 MET-h/week, premenopausal HR = 0.83, 95%CI = (0.70–0.99), postmenopausal HR = 0.86 (0.78–0.95); pheterogeneity = 0.97). Results were attenuated with adjustment for current body mass index (BMI) among postmenopausal, but not premenopausal, women (e.g., ≥ 27 vs < 3 MET-h/week, premenopausal HR = 0.83 (0.69–0.98); postmenopausal HR = 0.95 (0.85–1.05); pheterogeneity = 0.99). In analyses of moderate-vigorous activity and breast cancer risk, no heterogeneity by menopausal status was observed (phet ≥ 0.53; e.g., ≥ 27 vs < 3 MET-h/week, ER+/PR+, premenopausal HR = 0.88 (0.69–1.11); postmenopausal HR = 0.71 (0.58–0.88). No associations were observed for ER−/PR− disease.

Conclusions
Recreational physical activity was associated with lower breast cancer risk in both pre- and postmenopausal women, supporting recreational physical activity as an accessible, modifiable exposure associated with reduced breast cancer risk regardless of menopausal status.
Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assay
Authors: Wang Yinxi , Sun Wenwen , Karlsson Emelie , Kang Lövgren Sandy , Ács Balázs , Rantalainen Mattias , Robertson Stephanie , Hartman Johan 
Published: April 2024

Abstract
Purpose
To evaluate the Stratipath Breast tool for image-based risk profiling and compare it with an established prognostic multigene assay for risk profiling in a real-world case series of estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative early breast cancer patients categorized as intermediate risk based on classic clinicopathological variables and eligible for chemotherapy.

Methods
In a case series comprising 234 invasive ER-positive/HER2-negative tumors, clinicopathological data including Prosigna results and corresponding HE-stained tissue slides were retrieved. The digitized HE slides were analysed by Stratipath Breast.

Results
Our findings showed that the Stratipath Breast analysis identified 49.6% of the clinically intermediate tumors as low risk and 50.4% as high risk. The Prosigna assay classified 32.5%, 47.0% and 20.5% tumors as low, intermediate and high risk, respectively. Among Prosigna intermediate-risk tumors, 47.3% were stratified as Stratipath low risk and 52.7% as high risk. In addition, 89.7% of Stratipath low-risk cases were classified as Prosigna low/intermediate risk. The overall agreement between the two tests for low-risk and high-risk groups (N = 124) was 71.0%, with a Cohen’s kappa of 0.42. For both risk profiling tests, grade and Ki67 differed significantly between risk groups.

Conclusion
The results from this clinical evaluation of image-based risk stratification shows a considerable agreement to an established gene expression assay in routine breast pathology.
Percentages and reasons: AI explainability and ultimate human responsibility within the medical field
Authors: Herrmann Markus , Wabro Andreas , Winkler Eva 
Published: April 2024

AbstractWith regard to current debates on the ethical implementation of AI, especially two demands are linked: the call for explainability and for ultimate human responsibility. In the medical field, both are condensed into the role of one person: It is the physician to whom AI output should be explainable and who should thus bear ultimate responsibility for diagnostic or treatment decisions that are based on such AI output. In this article, we argue that a black box AI indeed creates a rationally irresolvable epistemic situation for the physician involved. Specifically, strange errors that are occasionally made by AI sometimes detach its output from human reasoning. Within this article it is further argued that such an epistemic situation is problematic in the context of ultimate human responsibility. Since said strange errors limit the promises of explainability and the concept of explainability frequently appears irrelevant or insignificant when applied to a diverse set of medical applications, we deem it worthwhile to reconsider the call for ultimate human responsibility.
Towards NICE-by-Design Cybersecurity Learning Environments: A Cyber Range for SOC Teams
Authors: Karagiannis Stylianos , Magkos Emmanouil , Karavaras Eleftherios , Karnavas Antonios , Nikiforos Maria Nefeli , Ntantogian Christoforos 
Published: April 2024

AbstractCybersecurity has become an increasingly important field as cyber threats continue to grow in number and complexity. The NICE framework, developed by NIST, provides a structured approach to cybersecurity education. Despite the publication of cybersecurity frameworks, scenario design in cybersecurity is not yet governed by structured design principles, leading to ambiguous learning outcomes. This research uses the NICE framework to provide structure design and development of a cyber range and the relevant scenarios. The proposed methodology and research results can assist the scenario design in cybersecurity and as a methodological procedure for evaluation. Finally, the research provides a better understanding of the NICE framework and demonstrates how it can assist in creating practical cybersecurity scenarios.
Grey Zone Healers and the COVID-19 Pandemic in Chechnya, Russia
Authors: Zakharova Evgenia , Kołodziejska Iwa , Kaliszewska Iwona 
Published: April 2024

AbstractThe Chechen authorities’ focus upon population health is enacted both through the principles of Islamic medicine and approved biomedical practices. Any healing practices beyond these domains are met with deep suspicion. Practitioners of unofficial complementary and alternative medicine healers may abruptly find themselves regarded as enemies of the state. In light of this precarious circumstance, it becomes pertinent to inquire: How do these healers employ their daily tactics to negotiate the intricate power dynamics between the formidable state apparatus and the established biomedical order? Drawing from our meticulous fieldwork conducted in the year 2021, we investigated the intricate tactics employed by unofficial healers in the Chechen medical landscape during COVID-19. Our research centred on discerning the nuanced tactics aimed at mitigating potential risks. We conclude that healers, having embodied tactics to creatively manoeuvre within the confines of the authoritarian state, perceived the challenges posed by COVID-19 as merely another, often inconsequential, obstacle in their enduring struggle.
Novel GCN Model Using Dense Connection and Attention Mechanism for Text Classification
Authors: Peng Yinbin , Wu Wei , Ren Jiansi , Yu Xiang 
Published: April 2024

AbstractConvolutional Neural Network (CNN) or Recurrent Neural Network (RNN) based text classification algorithms currently in use can successfully extract local textual features but disregard global data. Due to its ability to understand complex text structures and maintain global information, Graph Neural Network (GNN) has demonstrated considerable promise in text classification. However, most of the GNN text classification models in use presently are typically shallow, unable to capture long-distance node information and reflect the various scale features of the text (such as words, phrases, etc.). All of which will negatively impact the performance of the final classification. A novel Graph Convolutional Neural Network (GCN) with dense connections and an attention mechanism for text classification is proposed to address these constraints. By increasing the depth of GCN, the densely connected graph convolutional network (DC-GCN) gathers information about distant nodes. The DC-GCN multiplexes the small-scale features of shallow layers and produces different scale features through dense connections. To combine features and determine their relative importance, an attention mechanism is finally added. Experiment results on four benchmark datasets demonstrate that our model’s classification accuracy greatly outpaces that of the conventional deep learning text classification model. Our model performs exceptionally well when compared to other text categorization GCN algorithms.
Towards social life cycle assessment of food delivery: findings from the Italian case study
Authors: Ruggeri Marco , Zaki Mary Giò , Vinci Giuliana 
Published: April 2024

Abstract
Purpose
The growth of global food delivery (FD), which could reach a market value of 1510 billion dollars by 2027, could raise significant sustainability concerns, especially in terms of the social impact related to the expansion of the gig economy. This study, therefore, aims to analyze the social sustainability of the FD, taking Italy as a case study. The results could be a baseline to suggest practices that could promote a more socially responsible FD sector.

Methods
Social life cycle assessment (S-LCA) was used, following the guidelines of the Product Social Impact Life Cycle Assessment (PSILCA) and considering four categories of stakeholders (workers, value chain actors, society, and local community), 11 risk categories, and 13 subcategories, mainly based on both the availability of data and their adherence to the objectives of the study and FD.

Results and discussion
The main risks are associated with low wages, improper working hours, high accidentality, and approximation in food handling. Specifically, the wages of riders, 23% of whom are migrants, are just 14% above the poverty line in Italy and 67% below the median income. With 30-h work weeks, moreover, riders may face high risks of economic vulnerability. Stressful working conditions and the absence of mandatory protective equipment have resulted in 17 fatalities × 100,000 workers and 25 accidents × 1000 workers, which could generate a medium risk that violations of labor laws will occur. All this is also due to the low unionization in the Italian FD. Finally, results also show a flaw in food safety, as riders are not required to have HACCP and ATP attestation.

Conclusions
Italian legislation and the business models of FD companies are still shown to be insufficient to guarantee the fairness of protections for riders, which are substantiated by low wages, high accident rates, poor union rights, and improper working hours. In addition, doubts are raised about the hygiene of containers carrying food during transport, as they could induce a potential microbiological health risk for consumers, especially related to food handling during transport.
Advice to a Young Mathematical Biologist
Authors: Roberts Paul A. 
Published: April 2024

AbstractThis paper offers advice to early-mid career researchers in Mathematical Biology from ten past and current Presidents of the Society for Mathematical Biology. The topics covered include deciding if a career in academia is right for you; finding and working with a mentor; building collaborations and working with those from other disciplines; formulating a research question; writing a paper; reviewing papers; networking; writing fellowship or grant proposals; applying for faculty positions; and preparing and giving lectures. While written with mathematical biologists in mind, it is hoped that this paper will be of use to early and mid career researchers across the mathematical, physical and life sciences, as they embark on careers in these disciplines.
Development of an Incest Scale in the Turkish Language and Culture: Validity and Reliability Study
Authors: Bulut Meryem Berrin , Ömerca Beyza Naile , Polat Kübra , Kuzu Münevver 
Published: April 2024

AbstractThis study aims to develop a valid and reliable tool for measuring beliefs and attitudes regarding incest. Incest can be considered a widespread social problem. Despite the prevalence of incest, a tool that can measure knowledge of and attitudes toward incest in Turkey is still a necessity. In this study, 457 adults participated in the first and 255 adults in the second stage. To collect the data, Incest Scale, Childhood Emotional Incest Scale and demographic form were used. Exploratory/Confirmatory factor analysis, parallel analysis, reliability analysis were performed, and criterion validity was tested. A 23-item and 5-factor scale was obtained. The fit indexes obtained as a result of confirmatory factor analysis were satisfactory. Positive significant correlations were found between incest and childhood emotional incest. The reliability coefficients ​​were found to be within acceptable limits. This study is expected to fill a significant gap in the field, promote awareness regarding incest, and make an important contribution to the field to combat incest effectively.
Is mental regulation related to self-esteem? Testing a basic metacognitive model
Authors: Solheim Marte , Pukstad Erlend , Anyan Frederick , Strand Eivind R. , Nordahl Henrik 
Published: April 2024

AbstractIndividual differences in global self-esteem are associated with general psychological functioning and well-being, and lower self-esteem could be a target for prevention and treatment interventions. Traditionally, self-esteem is assumed to be influenced by the content of self-beliefs, but the metacognitive model of psychological disorders presents an alternative. It emphasizes mental regulation over the content in self-beliefs and suggests a role for metacognitive beliefs and corresponding metacognitive strategies. Thus, the metacognitive model has the potential to advance our understanding of self-esteem and provide new treatment interventions. Therefore, the aim of this study was to test a basic metacognitive model of self-esteem. In a cross-sectional design, 522 participants from a convenience sample completed a battery of self-report questionnaires. A metacognitive model where metacognitive strategies mediated the relationship between metacognitive beliefs and self-esteem was tested using structural equation modelling. Stronger endorsements of dysfunctional metacognitions were associated with more use of unhelpful metacognitive strategies, which further was significantly related to lower self-esteem. These relationships held even when controlling gender, age, anxiety, and personality traits as covariates. The results suggests that there is a role for dysfunctional metacognitive beliefs and strategies in self-esteem of which metacognitive strategies are the most proximal influence. This observation indicates that individual differences in mental regulation are relevant to understanding and possibly improving self-esteem. Interventions which effectively lead to metacognitive change are likely to have a positive effect on self-esteem.