bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perfusion estimation from dynamic non-contrast computed tomography using self-supervised learning and a physics-inspired U-net transformer architecture
Authors: Liu Yi-Kuan , Cisneros Jorge , Nair Girish , Stevens Craig , Castillo Richard , Vinogradskiy Yevgeniy , Castillo Edward 
Published: January 2025

Abstract

Purpose
Pulmonary perfusion imaging is a key lung health indicator with clinical utility as a diagnostic and treatment planning tool. However, current nuclear medicine modalities face challenges like low spatial resolution and long acquisition times which limit clinical utility to non-emergency settings and often placing extra financial burden on the patient. This study introduces a novel deep learning approach to predict perfusion imaging from non-contrast inhale and exhale computed tomography scans (IE-CT).

Methods
We developed a U-Net Transformer architecture modified for Siamese IE-CT inputs, integrating insights from physical models and utilizing a self-supervised learning strategy tailored for lung function prediction. We aggregated 523 IE-CT images from nine different 4DCT imaging datasets for self-supervised training, aiming to learn a low-dimensional IE-CT feature space by reconstructing image volumes from random data augmentations. Supervised training for perfusion prediction used this feature space and transfer learning on a cohort of 44 patients who had both IE-CT and single-photon emission CT (SPECT/CT) perfusion scans.

Results
Testing with random bootstrapping, we estimated the mean and standard deviation of the spatial Spearman correlation between our predictions and the ground truth (SPECT perfusion) to be 0.742 ± 0.037, with a mean median correlation of 0.792 ± 0.036. These results represent a new state-of-the-art accuracy for predicting perfusion imaging from non-contrast CT.

Conclusion
Our approach combines low-dimensional feature representations of both inhale and exhale images into a deep learning model, aligning with previous physical modeling methods for characterizing perfusion from IE-CT. This likely contributes to the high spatial correlation with ground truth. With further development, our method could provide faster and more accurate lung function imaging, potentially expanding its clinical applications beyond what is currently possible with nuclear medicine.
Harnessing complexity: integrating remote sensing and fuzzy expert system for evaluating land use land cover changes and identifying mangrove forest vulnerability in Bangladesh
Authors: Islam Md. Monirul , Al Rafi Dewan Abdullah , Jannat Arifa , Aruga Kentaka , Liebenehm Sabine , Hossain Radita 
Published: January 2025

Abstract
Purpose: This study analyzes Landsat images to examine the alterations in land cover within the Sundarbans and its surrounding regions in Bangladesh, spanning twenty-one years from 2000 to 2021. Furthermore, we develop a mangrove vulnerability map considering the combined effect of eight socioeconomic, geophysical, and climatic factors. Methods: Land use land cover (LULC) changes in the study area over a 21-year period were assessed using a random forest model, and the vulnerability analysis employed a fuzzy expert-based multicriteria decision-making (MCDM) approach. Results: The results show that a significant portion of the mangrove forest has been transformed into aquaculture practices because of the expansion of high-value shrimp cultivation. A decrease in forest areas and the expansion of aquaculture zones suggest a livelihood shift among the local population over time. This transition has adversely affected human activities within the ecosystem and the biodiversity of mangrove forests. Consequently, it is imperative to implement suitable measures to enhance the state of mangrove forests and safeguard their biodiversity. The vulnerability analysis shows that the highly vulnerable, moderately vulnerable, and low vulnerable areas cover 35.66%, 26.86%, and 19.42%, respectively. Conclusion: The vulnerability maps generated in this research could serve as a valuable resource for coastal planners seeking to ensure the sustainable stewardship of these coastal mangrove forests. These results offer a detailed understanding of coastal mangrove LULC patterns and vulnerability status, which will be useful for policymakers and resource managers to urgently incorporate into coastal land use and environmental management practices.
Epilepsy as a Wilding of Sleep
Authors: Szűcs Anna , Halász Péter 
Published: January 2025

Abstract

Purpose
To review the mutual links of sleep and epilepsy.

Recent Findings
It is supported in several ways that epilepsy is ‘born’ in sleep and evolves as its ‘wilding’. At least twelve to thirty percent of seizures occur during non-rapid eyemovement (NREM) sleep and interictal epileptiform activity accumulates during NREM sleep, paralleling homeostatic power and sleep pressure. The imbalance of sleep-related synaptic plasticity carries the risk of over-excitation and epileptic derailment. This is seen in major epilepsies, where normal NREM sleep patterns are shown to transform to epileptic discharges. Epilepsies then ‘strike back’ to sleep impairing its structure and functions. The harm of seizures is obvious; and interictal discharges even in seizure free patients may bring insidious and permanent loss of cognitive functions.

Conclusion
Sleep reveals the real face of epilepsy. Understanding the fine mechanisms of NREM sleep may lead to more effective epilepsy therapies and help reducing the harm of interictal activity as well.
Recent trends in spatial modeling studies of air quality (2010–2023)
Authors: Badawy Hesham 
Published: January 2025

Abstract
The fast growth of urbanization and increases in urban populations have greatly affected air quality, creating a significant challenge for both the environment and public health in urban areas. Consequently, it has become essential to understand and evaluate the levels and impacts of air pollution in these regions for the purpose of sustainable urban development. This study explores recent advancements in spatial air quality research spanning from 2010 to 2023, synthesizing findings from various sources. To accomplish this, the study employs a comprehensive methodology that includes bibliometric analysis to measure research output and identify publication trends, content analysis to extract thematic insights from the literature, case studies to analyze applied models in practical situations, and survey analysis. The findings emphasize important research directions in the field of spatial air quality modeling, with a particular focus on health impact assessments, which are a recurring theme throughout the studies reviewed. Other essential areas of emphasis include predictions concerning emerging pollutants, assessments of indoor air quality in urban settings, and the effects of natural disasters specifically forest fires and dust storms on air quality. The study emphasizes progress in high-precision modeling, the incorporation of machine learning techniques, and the integration of climate change projections. Despite these advancements, notable gaps remain in the existing literature, especially concerning the scarcity of studies on emerging contaminants such as nanoparticles and persistent organic pollutants, and limited attention given to rural and developing regions. These gaps emphasize the necessity for interdisciplinary models that combine real-time data related to health, environmental concerns, and socioeconomic factors to improve the robustness and applicability of models. This paper emphasizes the significance of sustained access to real-time air quality data in assisting knowledgeable decision-making processes. It accentuates the essential necessity of enhancing awareness regarding the relationships among air quality, public health, and environmental well-being.
A Person-Centered Study of Construction Sector Workers’ Goal Orientation Profiles and Their Connections to Approaches to Learning, Self-efficacy, and Work Engagement
Authors: Puhakka Ilmari J. A. , Niemivirta Markku , Postareff Liisa , Nokelainen Petri 
Published: January 2025

Abstract
This study uses a person-centered approach to investigate construction workers’ learning at work, focusing on their approaches to learning, self-efficacy beliefs and work engagement and how these vary according to their goal orientation profiles. Survey data were collected from Finnish construction sector employees (N = 1,280) in June 2021. The data were analysed using latent profile analysis (LPA). Analyses revealed four goal orientation profiles: Disengaged (19.1%), Avoidance-oriented (2.1%), Performance-oriented (43.0%) and Mastery-oriented (35.7%). Profiles based on high learning orientation (Performance-oriented, Mastery-oriented) had higher emphasis on a deep approach to learning, as well as higher self-efficacy and work engagement. The profiles differed less regarding unreflective approach to learning. The results illuminate construction workers’ learning processes in terms of learning strategies and motivation and how they compare to those of the more extensively studied student population. The results also encourage finding ways to support workers’ mastery orientation to benefit not only learning but also well-being by enhancing more reflective learning approaches.
Yield of family screening for dilated cardiomyopathy: 10-year experience at a multidisciplinary cardiogenetic outpatient clinic
Authors: Thierry Isabelle P. , Muller Steven A. , Baas Annette F. , Dooijes Dennis , van Loon R. Laura E. , Schoemaker Angela E. , van der Harst Pim , Oerlemans Marish I. F. J. , Baars Hubert F. , Hassink Rutger J. , Asselbergs Folkert W. , van Tintelen J. Peter , te Riele Anneline S. J. M. 
Published: January 2025

Abstract

Introduction
Current family screening approaches in dilated cardiomyopathy (DCM) depend on the presence or absence of a familial genetic variant, in which variant pathogenicity (i.e. benign or pathogenic) classification drives screening recommendations. However, this approach has never been systematically evaluated.

Methods
To describe the yield of DCM family screening stratified by variant classification in the Netherlands, we included 358 relatives (mean age ± standard deviation: 44.4 ± 15.9 years at baseline; 52% female; 41% (likely) pathogenic (LP/P) variant carriers from 210 families). Demographics, symptoms and genetic/cardiac test results were obtained. Endpoints were the development of DCM (left ventricular ejection fraction < 50% of non-ischaemic aetiology) or occurrence of major adverse cardiovascular events (MACE) (i.e. heart failure hospitalisation, ventricular arrhythmia or death). Probability of DCM or MACE was assessed with the Kaplan-Meier method.

Results
DCM was present in 32 relatives (9%) (25/32 (78%) with LP/P variant) at baseline and in an additional 10/97 relatives (10%) (9/10 (90%) with LP/P variant) who were re-evaluated during a median follow-up time of 5.0 years (interquartile range: 3.2–7.4). Of the 128 relatives without the familial LP/P variant, none developed DCM. MACE was experienced by 5 relatives (1%) (4/5 (80%) with LP/P variant), all of whom had DCM at the time of the event.

Conclusion
The yield of DCM family screening was ~10% at baseline and another ~10% during 5‑year follow-up. Relatives without the familial LP/P variant could be safely discharged. These results reinforce the use of a genetics-first screening approach in relatives from families with an LP/P variant. This will lower the burden on resources in Dutch hospitals and help allocate resources to those who are most likely to benefit.
Crafting congruence: towards systematic scenario design in maritime simulator training and assessment
Authors: Harrington Susan , Sellberg Charlott , Lindwall Oskar 
Published: January 2025

Abstract
In this study, we explore the current practices of experienced instructors in developing scenarios for maritime simulator training and assessment. Scenario design is fundamental to effective simulator-based training but remains underexplored in extant literature. Through a series of semi-structured interviews (n = 16), we identify the core concerns of instructors designing scenarios; (1) realism, authenticity, and fidelity; (2) designing for students’ requirements; (3) the importance of clear learning objectives. Based on the results, we propose that functional congruence is a more fitting term than realism, authenticity, and fidelity in this context, as effective simulator training requires a balance between a simulator realistic enough for immersive learning experiences, and a focus on clear learning objectives. In consideration of the need to train students to function as part of a team of competent experts, moreover, we propose the introduction of an established instructional design model into the scenario design process. The proposed model has proven successful in simulator-based training in the similarly high-risk and safety-critical field of healthcare and has the potential to both complement the current practices of experienced instructors and act as a valuable resource for those newer to the role in designing training transferrable to professional practice.
Rapid Grain Segmentation of Heat-treated and Annealed LPBF Haynes 282 Using an Unsupervised Learning-Based Computer Vision Approach
Authors: Yi Yu-Tsen , Seo Junwon , Murphy Kevin , Rollett Anthony 
Published: January 2025

Abstract
Grain size distribution is a critical factor in determining materials’ physical and mechanical properties, including thermal conductivity, hardness, and creep behavior. Understanding the distribution of grain sizes is essential for advancing the comprehension of material properties and improving materials development and design. Traditional methods for determining grain size, such as electron backscatter diffraction (EBSD), are resource-intensive, underscoring the need for more efficient approaches to grain segmentation in standard micrographs, such as those obtained via SEM and optical imaging. This paper presents a streamlined, unsupervised computer vision pipeline that employs superpixel segmentation and region adjacency merging techniques to segment and measure grain geometry from micrographs efficiently. The pipeline is validated using two methods: hand-labeled SEM images of laser powder bed fusion (LPBF) fabricated Haynes 282 Ni-alloy and open-source EBSD data of IN100 from Dream3D. Both validation approaches achieved IoU and Dice scores greater than 0.9, while processing an image with a resolution of 1000 × 1000 pixels in under 40 s, demonstrating a fast and sufficiently accurate pipeline.
The impact of utility-scale RES power production on the Italian electricity prices
Authors: Alessi Damiano , Bonaldo Cinzia , Fontini Fulvio 
Published: January 2025

Abstract
The rise of power production from non-programmable renewable power sources imply a reduction in power price and an increasing stress to the power system. In the paper the impact of new investments in variable renewable energy sources on the Italian electricity system is evaluated. In order to do so, demand and supply curves of the day-ahead market of some representative days and periods of the year are simulated taking into account the introduction of new solar and wind power plants in the offer curve, as well the zonal configuration of the Italian market and the transmission constraints. Results show that new renewable investments significantly affect electricity prices but only in the southernmost Italian zones. However, the North zone, which accounts for the majority of all Italian load, shows a comparatively lower benefit from the investments, particularly in those months and hours of the day in which there is a limited supply of wind power. Limited transmission capacity to transfer power from the south towards north of Italy worsen this. Conversely, the southernmost zones and islands benefit from photovoltaic and wind power investments, reducing prices. However, high production in these regions, coupled with transmission constraints, leads also to high curtailments when generation exceeds demand. Finally, the planned transmission capacity expansion is also considered. It is shown that it further reduces the prices in the northernmost zones, yet it is not enough to fully transfer the positive impact on prices in southernmost zones or to reduce the curtailments, which can be as high as 60% of the new capacity in some zones.
Investigating novel material additives for improved radiation shielding in ultra-high performance cement mortars
Authors: Korkmaz Abdul Vahap , Akkurt İskender 
Published: January 2025

Abstract
In recent years, heavy concrete has been widely used in industry due to the growing application of nuclear technology and the harmful effects of atomic radiation, such as gamma rays, on the environment. The primary component of concrete is cement, which is the critical factor that determines the most important properties of concrete, such as durability, hardness, and structural integrity. This study suggests that metaschist-modified cement (Portland Cement, CEM I 52.5 N) produced using traditional cement manufacturing methods may offer an alternative to ordinary cement clay-mixed cement (Portland Cement CEM I 52.5 N) for radiation protection in nuclear energy applications. This study comprehensively investigated materials such as ordinary cement clay and metaschist, which can be potentially used to protect radioactive substances in cement mortars. Mortars produced using micronized metaschist (MSC) and ordinary cement clay (OCC) were analyzed at different energy levels. The mass attenuation coefficient (MAC) of cement samples was determined experimentally using various radioactive point sources. Additionally, hydraulic and mechanical tests were conducted based on cement standards (TSE EN 196-1, TS EN 196-3, and TS EN 196-6) to evaluate the performance of the produced cement samples. The results indicate that the metaschist-modified Portland cement (MMPC-52,5/N) mixture demonstrates superior radioactive shielding performance compared to ordinary cement clay-mixed cement (Ordinary Portland Cement, CEM I 52.5 N). Cement samples containing MMPC-52,5/N demonstrate superior performance characteristics and high radiation shielding properties, indicating significant potential for applications in nuclear technology.
Macadamia biowaste-derived adsorbents for application in water treatment and gas sensing: the current status. Rapid review 2014 to 2024
Authors: Pakade Vusumzi Emmanuel 
Published: January 2025

Abstract
The production and consumption of macadamia nuts and oil have escalated over the past few years. Macadamia nuts and oil are rich in minerals and have been linked to lower blood cholesterol levels and a reduced risk of heart disease. The production of nutshell by-products, which require long-term environmental management, has expanded in tandem with the harvesting of nuts and oil. One of the strategies adopted to beneficiate the nutshells is the creation of adsorbents to capture gases, metal ions, and organic pollutants. As a result, macadamia-based adsorbents are currently gaining popularity for a variety of applications. This paper reviews the utilization of macadamia adsorbents in water remediation, gas capture, and fuel cells. The review summarizes the current status and predicts future developments. According to the data gathered in this review, the removal of Cr(VI) and methylene blue appears to be popular among researchers, while other metals and organic compounds have received very little attention. In fact, there is a paucity of data relating to use of macadamia-based adsorbents to remove pharmaceuticals and other emerging contaminants. Although satisfactory adsorption performance for a few pollutants has been reported, the technique still requires further development and extension to other pollutants and applications.
Developing high-voltage flexible diodes by nitrogen-doped sputtering of silicon carbide onto buckypaper and grapheme paper, and investigating its thermoelectric and photoelectric voltage effects
Authors: Lin Chia-Yi , Liu Jih-Hsin 
Published: January 2025

Abstract
This paper investigates the development and characterization of high-voltage PN diodes using nitrogen-doped silicon carbide (N-SiC) deposited on carbon nanotube paper (BP) and graphene paper (GP), respectively. The process involves fabricating flexible semiconductor substrates made of carbon materials, specifically BP composed of multi-walled carbon nanotubes (MWCNTs) and GP produced from multilayer graphene powder. Material properties were analyzed using Raman spectroscopy, Hall measurements, scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS). Electrical characteristics revealed that the diode fabricated with 20 min of N-SiC sputtering on BP exhibited a reverse breakdown voltage of -476 volts, surpassing that of the diode based on GP, which showed a reverse breakdown voltage of -88 volts. Moreover, this study underscores the significance of N-SiC deposition in modulating the properties of carbon-based materials and provides insights into the high-temperature thermoelectric and photoelectric effects of high-voltage carbon material diodes.
Reconstructing the Map: A Neopragmatist Perspective on Cartography in the Context of Artificial Intelligence (AI)
Authors: Kühne Olaf , Edler Dennis 
Published: January 2025

Abstract
The present article explores possibilities for a new theoretical framework in cartography based on a neopragmatist approach. Starting with an outline of Traditional and Critical Cartography, a neopragmatist perspective is developed that promotes inclusivity and problem-solving orientation. This approach draws on the analytical framework of Karl Popper’s Three Worlds Theory, specifically the Theory of Three Spaces. Neopragmatism emphasizes the production of useful knowledge over absolute truth and acknowledges the contingency and flexible interpretability of cartographic representations. In this context, Artificial Intelligence (AI) is described as a dynamic tool for problem-solving, capable of supporting continuous learning and application-oriented adaptation. By employing AI within a neopragmatist framework in cartography, new possibilities emerge for integrating and utilizing diverse social perspectives and (geospatial) data. This approach enables an expansion of the theoretical and practical applicability of cartography. Finally, the article illustrates that the deconstruction—building on J. B. Harley’s influential article Deconstructing the Map (1989)—and reconstruction of maps must exist in a recursive relationship to enable a context- and solution-oriented cartography.