bluuebunny/crossref_metadata_2025_split huggingface dataset:
Animal spirits, bankruptcies, and monetary policy effectiveness in a hybrid macroeconomic agent-based financial accelerator model
Authors: Bazzana Davide 
Published: April 2024

AbstractThis paper develops a hybrid model with an agent-based financial accelerator framework embedded in a standard new Keynesian economy. It explores the interactions between the financial accelerator and the credit market, focusing on the effects of bankruptcy. The paper replicates credit-market relationships, modeling various credit crunch scenarios. It uncovers endogenous fluctuations and “animal spirits” in entrepreneurs’ expectations, driving investment and production decisions. Notably, higher pro-cyclical leverage can have destabilizing effects in the presence of small shocks, increasing entrepreneurs’ bankruptcies. The results suggest that monetary policy’s effectiveness in stabilizing fluctuations depends on factors such as heterogeneity, bounded rationality, and heuristic updating mechanisms. Moderate monetary policies perform better in terms of economic growth with moderate-to-low volatility, while aggressive policies on inflation assist bounded rational agents in reducing errors in investment decisions and default rates, fostering a more stable macroeconomic environment. Increasing forecasting options introduces diversification among entrepreneurs, reducing volatility and stabilizing investments. More options mitigate investment fluctuations, acting as a counterbalance to prevailing market sentiments. Over time, individuals weakly adhering to trends or adopting contrarian approaches come to dominate the population of entrepreneurs, enhancing the overall stability of investment decisions.
Synthesis and preclinical evaluation of novel 18F-vancomycin-based tracers for the detection of bacterial infections using positron emission tomography
Authors: Spoelstra G. B. , Blok S. N. , Reali Nazario L. , Noord L. , Fu Y. , Simeth N. A. , IJpma F. F. A. , van Oosten M. , van Dijl J. M. , Feringa B. L. , Szymanski W. , Elsinga P. H. 
Published: April 2024

Abstract
Introduction
Bacterial infections are a major problem in medicine, and the rapid and accurate detection of such infections is essential for optimal patient outcome. Bacterial infections can be diagnosed by nuclear imaging, but most currently available modalities are unable to discriminate infection from sterile inflammation. Bacteria-targeted positron emission tomography (PET) tracers have the potential to overcome this hurdle. In the present study, we compared three 18F-labelled PET tracers based on the clinically applied antibiotic vancomycin for targeted imaging of Gram-positive bacteria.

Methods
[18F]FB-NHS and [18F]BODIPY-FL-NHS were conjugated to vancomycin. The resulting conjugates, together with our previously developed [18F]PQ-VE1-vancomycin, were tested for stability, lipophilicity, selective binding to Gram-positive bacteria, antimicrobial activity and biodistribution. For the first time, the pharmacokinetic properties of all three tracers were compared in healthy animals to identify potential binding sites.

Results
[18F]FB-vancomycin, [18F]BODIPY-FL-vancomycin, and [18F]PQ-VE1-vancomycin were successfully synthesized with radiochemical yields of 11.7%, 2.6%, and 0.8%, respectively. [18F]FB-vancomycin exhibited poor in vitro and in vivo stability and, accordingly, no bacterial binding. In contrast, [18F]BODIPY-FL-vancomycin and [18F]PQ-VE1-vancomycin showed strong and specific binding to Gram-positive bacteria, including methicillin-resistant Staphylococcus aureus (MRSA), which was outcompeted by unlabeled vancomycin only at concentrations exceeding clinically relevant vancomycin blood levels. Biodistribution showed renal clearance of [18F]PQ-VE1-vancomycin and [18F]BODIPY-FL-vancomycin with low non-specific accumulation in muscles, fat and bones.

Conclusion
Here we present the synthesis and first evaluation of the vancomycin-based PET tracers [18F]BODIPY-FL-vancomycin and [18F]PQ-VE1-vancomycin for image-guided detection of Gram-positive bacteria. Our study paves the way towards real-time bacteria-targeted diagnosis of soft tissue and implant-associated infections that are oftentimes caused by Gram-positive bacteria, even after prophylactic treatment with vancomycin.
Barriers and facilitators to implementation of an exercise and education programme for osteoarthritis: a qualitative study using the consolidated framework for implementation research
Authors: Bhardwaj Avantika , FitzGerald Christine , Graham Margaret , MacFarlane Anne , Kennedy Norelee , Toomey Clodagh M. 
Published: April 2024

AbstractTargeted efforts to better understand the barriers and facilitators of stakeholders and healthcare settings to implementation of exercise and education self-management programmes for osteoarthritis (OA) are needed. This study aimed to explore the barriers and facilitators to the implementation of Good Life with osteoArthritis in Denmark (GLA:D), a supervised group guideline-based OA programme, across Irish public and private healthcare settings. Interviews with 10 physiotherapists (PTs; 8 public) and 9 people with hip and knee OA (PwOA; 4 public) were coded by the Consolidated Framework for Implementation Research (CFIR) constructs in a case memo (summary, rationale, quotes). The strong positive/negative implementation determinants were identified collaboratively by rating the valence and strength of CFIR constructs on implementation. Across public and private settings, PTs and PwOA strongly perceived GLA:D Ireland as evidence-based, with easily accessible education and modifiable marketing/training materials that meet participants’ needs, improve skills/confidence and address exercise beliefs/expectations. Despite difficulties in scheduling sessions (e.g., work/caring responsibilities), PTs in public and private settings perceived advantages to implementation over current clinical practice (e.g., shortens waiting lists). Only PTs in public settings reported limited availability of internal/external funding, inappropriate space, marketing/training tools, and inadequate staffing. Across public and private settings, PwOA reported adaptability, appropriate space/equipment and coaching/supervision, autonomy, and social support as facilitators. Flexible training and tailored education for stakeholders and healthcare settings on guideline-based OA management may promote implementation. Additional support on organising (e.g., scheduling clinical time), planning (e.g., securing appropriate space, marketing/training tools), and funding (e.g., accessing dedicated internal/external grants) may strengthen implementation across public settings.
Dispersal potential does not predict recent range expansions of sub-Antarctic plant species
Authors: Mazibuko Nompilo , Greve Michelle , le Roux Peter C. 
Published: April 2024

AbstractDispersal influences many key aspects of plant ecology at both fine- and broad scales. However, dispersal events are challenging to quantify as they are difficult to observe and measure accurately, despite the importance of understanding species’ dispersal capacity. In this study, we quantified dispersal estimates for the dominant vascular flora of sub-Antarctic Marion Island, using a mechanistic model to estimate dispersal potential via anemochory and standardized experiments that simulate dispersal events via zoochory, human activity, and thalassochory, to test if dispersal capacity correlates to contemporary range expansion of the island’s native and alien species. Our results demonstrate the broad range of dispersal potential in the island’s flora and represent the first quantification of the dispersal potential (via multiple vectors) of the dominant vascular flora in the sub-Antarctic. Dispersal potential was not related to range expansion rates of native or alien species, suggesting that other mechanisms are responsible for the variation observed in species range expansion rates. Although this finding contradicts expectations and evidence from some other studies, it is consistent with research conducted in alpine regions (which may be climatically and physiognomically similar to this sub-Antarctic study site) where factors such as demography and competition are more important predictors of species range expansion than their dispersal ability, dispersal syndromes, or dispersal-related traits.
Ultrastructure and phylogenetic significance of spermatozoa in Nemertea
Authors: Bartolomaeus Thomas , Bronkars Vanessa , Adam Leon , von Döhren Jörn 
Published: April 2024

AbstractSperm ultrastructure is frequently employed as a source for phylogenetic inference due to the ease of accessing spermatozoa. Despite being unicellular, sperm cells exhibit a relatively high number of diverse characters and character states. Spermatozoa are subject to strong sexual selection as they are finely tuned for maximizing male reproductive success. Given this strong functional constraint, one might anticipate the emergence of convergent characters in line with similar modes of reproduction. As a result, it might be expected that sperm cells do not possess substantial phylogenetic signal, with functional constraints overshadowing any evolutionary heritage. To test this assumption, we conducted a study on sperm ultrastructure in 11 nemertean species, representing closely related groups and major nemertean lineages. We analyzed these data for their phylogenetic signal within the context of the most recent nemertean phylogenies. Our findings demonstrate that, at all systematic levels, functional constraints imposed by sexual selection, or the mode of reproduction do not supersede the influence of historical constraints on sperm ultrastructure.
The role of food during oncology treatment: perspectives of cancer patients, caregivers and healthcare professionals
Authors: Adamczyk Dominika , Maison Dominika , Lignou Stella , Oloyede Omobolanle O. , Clegg Miriam , Methven Lisa , Fairfield Carol , Gosney Margot , Hernando Maria José , Amézaga Javier , Caro Mercedes , Tueros Itziar 
Published: April 2024

Abstract
Purpose
Many cancer patients have problems eating which are usually connected to taste and smell alterations due to side effects of cancer treatment. These problems have consequences both in terms of malnutrition and reduced quality of life. In order to explore social and psychological consequences of eating problems in cancer patients, qualitative interviews were conducted with cancer patients, their caregivers and healthcare professionals.

Methods
The study was conducted in three European countries (Poland, Spain and the UK) that differed in culture, oncology care approaches and availability of nutritional products targeted to cancer patients in the market.

Results
Differences in the social role of eating between the three European countries were observed which subsequently influenced the impact of eating problems for cancer patients in these countries. Furthermore, the study found that problems with food affect not only the quality of life of cancer patients, but can also distress their caregivers, who are often unable to cope with such food-related problems. In addition, the study showed that commercially available nutritional products for cancer patients focus on nutritional value but tend to neglect an important aspect of eating, which is the enjoyment of food, both individually and socially.
End-to-end tire defect detection model based on transfer learning techniques
Authors: Saleh Radhwan A. A. , Konyar Mehmet Zeki , Kaplan Kaplan , Ertunç H. Metin 
Published: April 2024

AbstractVisual inspection of defective tires post-production is vital for human safety, as faulty tires can lead to explosions, accidents, and loss of life. With the advancement of technology, transfer learning (TL) plays an influential role in many computer vision applications, including the tire defect detection problem. However, automatic tire defect detection is difficult for two reasons. The first is the presence of complex anisotropic multi-textured rubber layers. Second, there is no standard tire X-ray image dataset to use for defect detection. In this study, a TL-based tire defect detection model is proposed using a new dataset from a global tire company. First, we collected and labeled the dataset consisting of 3366 X-ray images of faulty tires and 20,000 images of qualified tires. Although the dataset covers 15 types of defects arising from different design patterns, our primary focus is on binary classification to detect the presence or absence of defects. This challenging dataset was split into 70, 15, and 15% for training, validation, and testing, respectively. Then, nine common pre-trained models were fine-tuned, trained, and tested on the proposed dataset. These models are Xception, InceptionV3, VGG16, VGG19, ResNet50, ResNet152V2, DenseNet121, InceptionResNetV2, and MobileNetV2. The results show that the fine-tuned VGG19, DenseNet21 and InceptionNet models achieve compatible results with the literature. Moreover, the Xception model outperformed the compared TL models and literature methods in terms of recall, precision, accuracy, and F1 score. Moreover, it achieved on the testing dataset 73.7, 88, 80.2, and 94.75% of recall, precision, F1 score, and accuracy, respectively, and on the validation dataset 73.3, 90.24, 80.9, and 95% of recall, precision, F1 score, and accuracy, respectively.
Numerical investigation of crack propagation regimes in snow fracture experiments
Authors: Bobillier Grégoire , Bergfeld Bastian , Dual Jürg , Gaume Johan , van Herwijnen Alec , Schweizer Jürg 
Published: April 2024

AbstractA snow slab avalanche releases after failure initiation and crack propagation in a highly porous weak snow layer buried below a cohesive slab. While our knowledge of crack propagation during avalanche formation has greatly improved over the last decades, it still remains unclear how snow mechanical properties affect the dynamics of crack propagation. This is partly due to a lack of non-invasive measurement methods to investigate the micro-mechanical aspects of the process. Using a DEM model, we therefore analyzed the influence of snow cover properties on the dynamics of crack propagation in weak snowpack layers. By focusing on the steady-state crack speed, our results showed two distinct fracture process regimes that depend on slope angle, leading to very different crack propagation speeds. For long experiments on level terrain, weak layer fracture is mainly driven by compressive stresses. Steady-state crack speed mainly depends on slab and weak layer elastic moduli as well as weak layer strength. We suggest a semi-empirical model to predict crack speed, which can be up to 0.6 times the slab shear wave speed. For long experiments on steep slopes, a supershear regime appeared, where the crack propagation speed reached approximately 1.6 times the slab shear wave speed. A detailed micro-mechanical analysis of stresses revealed a fracture principally driven by shear. Overall, our findings provide new insight into the micro-mechanics of dynamic crack propagation in snow, and how these are linked to snow cover properties.
Graphical Abstract
Customizing ICU patient monitoring: a user-centered approach informed by nurse profiles
Authors: Bostan Idil , van Egmond René , Gommers Diederik , Özcan Elif 
Published: April 2024

AbstractIntensive Care Unit (ICU) nurses are burdened by excessive number of false and irrelevant alarms generated by patient monitoring systems. Nurses rely on these patient monitoring systems for timely and relevant medical information concerning patients. However, the systems currently in place are not sensitive to the perceptual and cognitive abilities of nurses and thus fail to communicate information efficiently. An efficient communication and an effective collaboration between patient monitoring systems and ICU nurses is only possible by designing systems sensitive to the abilities and preferences of nurses. In order to design these sensitive systems, we need to gain in-depth understanding of the user group through revealing their latent individual characteristics. To this end, we conducted a survey on individual characteristics involving nurses from two IC units. Our results shed light on the personality and other characteristics of ICU nurses. Subsequently, we performed hierarchical cluster analysis to develop data-driven nurse profiles. We suggest design recommendations tailored to four distinct user profiles to address their unique needs. By optimizing the system interactions to match the natural tendencies of nurses, we aspire to alleviate the cognitive burden induced by system use to ensure that healthcare providers receive relevant information, ultimately improving patient safety.
Validation and extension of two domain-specific information privacy competency models
Authors: Soumelidou Aikaterini , Tsohou Aggeliki 
Published: April 2024

AbstractThe purpose of this paper is to validate two domain-specific information privacy competency models (IPCMs); the first for online consumers and the second for users of mobile applications (apps). For the validation of the competency models, we conducted qualitative research, using interviews to collect feedback by a group of nine information privacy experts. Regarding the evaluation, the experts commented largely positively for the structure and content of the IPCMs, as well as for the extent to which they achieve the intended goals. They also provided several points for improvements, which resulted in enhancing the quality of both IPCMs. The validation of the domain-specific demonstrated that this is the first study to empirically examine the privacy competencies that users of specific technological contexts should hold. The IPCMs can be used not only by educators and privacy policy makers for the design of privacy interventions, but also by e-commerce and mobile-apps providers, who could gain important insights into the way that they can be more reliable for their users. Both consumers and users of mobile-apps could benefit from IPCMs by acquiring the necessary privacy competencies through training programs for the protection of their information privacy.
Construction of a meteorological application system based on BDS ground-based augmentation network and water vapor products validation
Authors: Du Mingbin , Cao Yunchang , Liang Hong , Hu Heng , Wang Haishen , Song Shuli , Jiao Guoqiang 
Published: April 2024

AbstractThe national Beidou Navigation Satellite System (BDS) ground-based augmentation network (BGAN) of China is constructed with the existing GNSS observation resources of industrial sectors and local governments, based on the concept of joint building and sharing with sustainable development. This study provides a detailed introduction to the design, construction and operation of a meteorological application system based on BGAN, and validation of its water vapor products. BDS and GPS real-time observation of atmospheric water vapor is achieved nationwide in China and multi-GNSS applications. Through the application of multi-GNSS data and validation of the water vapor products from 2018 to 2020, the accuracy of precipitable water vapor (PWV) derived from BDS only is equivalent to that from GPS only. The root mean square error (RMSE) between them is about 2 mm with high correlation coefficient. Based on radiosonde data, the validation is conducted with the products of BDS-PWV, GPS-PWV, and Combined-PWV derived with multi-GNSS of BDS and GPS. The error characteristics of the three products show a consistent trend over the months. The bias is relatively small. The RMSE of the three products is in the range of 2.18–2.73 mm. The BDS-PWV has the largest RMSE, followed by GPS-PWV, and Combined-PWV has the smallest RMSE.
More than a simple fixed action pattern: Yawning in drills
Authors: Galotti Alice , Fausti Giulia , Casetta Grazia , Nolfo Andrea Paolo , Maglieri Veronica , Palagi Elisabetta 
Published: April 2024

AbstractIn the last decade, increasing attention has been devoted to exploring some aspects of yawning in non-human animals. With their chin red mark, bony paranasal swellings, male large brains and long canines, drills (Mandrillus leucophaeus) offer a robust model for testing hypotheses on the phenomenon. We identified two yawn variants (covered, YCT and uncovered teeth, YUCT) which differ in terms of recruitment of muscular action units (AUs). We tested the effects of several variables (sex, dominance rank, context) on the duration of the yawn and the probability of YCT or YUCT occurrence. We found that males performed longer and more YUCT than females. These findings support the Brain Cooling Hypothesis suggesting that those species showing large brains tend to display larger and longer yawns. We also tested the State Changing Hypothesis predicting the presence of a temporal association of yawning and ongoing behavioral transitions. A sequential analysis revealed that after 30 s following a yawn, drills were significantly more likely to change their behavioral state. Through the observation of yawning, conspecifics might gain knowledge of impending state changes. Seeing other’s yawns increased the probability of a similar response in the observers, thus suggesting the presence of yawn contagion in drills. Although the dataset needs to be expanded, our findings indicate that yawning is variable in drills, it can be associated with subjects’ state changes, and the imminent shifts can be perceived/processed by conspecifics.
Graphical Abstract
Multi-factor stock trading strategy based on DQN with multi-BiGRU and multi-head ProbSparse self-attention
Authors: Liu Wenjie , Gu Yuchen , Ge Yebo 
Published: April 2024

Abstract
Reinforcement learning is widely used in financial markets to assist investors in developing trading strategies. However, most existing models primarily focus on simple volume-price factors, and there is a need for further improvement in the returns of stock trading. To address these challenges, a multi-factor stock trading strategy based on Deep Q-Network (DQN) with Multi-layer Bidirectional Gated Recurrent Unit (Multi-BiGRU) and multi-head ProbSparse self-attention is proposed. Our strategy comprehensively characterizes the determinants of stock prices by considering various factors such as financial quality, valuation, and sentiment factors. We first use Light Gradient Boosting Machine (LightGBM) to classify turning points for stock data. Then, in the reinforcement learning strategy, Multi-BiGRU, which holds the bidirectional learning of historical data, is integrated into DQN, aiming to enhance the model’s ability to understand the dynamics of the stock market. Moreover, the multi-head ProbSparse self-attention mechanism effectively captures interactions between different factors, providing the model with deeper market insights. We validate our strategy’s effectiveness through extensive experimental research on stocks from Chinese and US markets. The results show that our method outperforms both temporal and non-temporal models in terms of stock trading returns. Ablation studies confirm the critical role of LightGBM and multi-head ProbSparse self-attention mechanism. The experiment section also demonstrates the significant advantages of our model through the presentation of box plots and statistical tests. Overall, by fully considering the multi-factor data and the model’s feature extraction capabilities, our work is expected to provide investors with more precise trading decision support.

Graphical abstract