bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Remark on the Spherical Bipartite Spin Glass
Authors: Genovese Giuseppe 
Published: May 2022

AbstractAuffinger and Chen (J Stat Phys 157:40–59, 2014) proved a variational formula for the free energy of the spherical bipartite spin glass in terms of a global minimum over the overlaps. We show that a different optimisation procedure leads to a saddle point, similar to the one achieved for models on the vertices of the hypercube.
Kyushu Decorative Tumuli Project: From e-Heritage to Cyber-Archaeology
Authors: Ikeuchi Katsushi , Morimoto Tetsuro , Kamakura Mawo , Kuchitsu Nobuaki , Kawano Kazutaka , Ikeda Tomoo 
Published: May 2022

AbstractDigitization of cultural assets has become an important sub-area of computer vision (CV). Thus far, the value of digitization has been emphasized in terms of asset preservation and exhibition. The third aspect of digitization value is that the obtained digital data can be used to perform archaeological analysis based on physics and optics theories and simulations. This position paper emphasizes the importance of this third aspect, using our Kyushu decorative tumuli project as an illustrative example. In particular, we focus on the photometric approaches in the third aspect and explain the equipment and methods developed there as well as archaeological findings. This paper, then, proposes to establish this area as “cyber-archaeology” through categorizing and organizing those methodologies.
Data-centric multi-task surgical phase estimation with sparse scene segmentation
Authors: Sanchez-Matilla Ricardo , Robu Maria , Grammatikopoulou Maria , Luengo Imanol , Stoyanov Danail 
Published: May 2022

Abstract
Purpose
Surgical workflow estimation techniques aim to divide a surgical video into temporal segments based on predefined surgical actions or objectives, which can be of different granularity such as steps or phases. Potential applications range from real-time intra-operative feedback to automatic post-operative reports and analysis. A common approach in the literature for performing automatic surgical phase estimation is to decouple the problem into two stages: feature extraction from a single frame and temporal feature fusion. This approach is performed in two stages due to computational restrictions when processing large spatio-temporal sequences.

Methods
The majority of existing works focus on pushing the performance solely through temporal model development. Differently, we follow a data-centric approach and propose a training pipeline that enables models to maximise the usage of existing datasets, which are generally used in isolation. Specifically, we use dense phase annotations available in Cholec80, and sparse scene (i.e., instrument and anatomy) segmentation annotation available in CholecSeg8k in less than 5% of the overlapping frames. We propose a simple multi-task encoder that effectively fuses both streams, when available, based on their importance and jointly optimise them for performing accurate phase prediction.

Results and conclusion
We show that with a small fraction of scene segmentation annotations, a relatively simple model can obtain comparable results than previous state-of-the-art and more complex architectures when evaluated in similar settings. We hope that this data-centric approach can encourage new research directions where data, and how to use it, plays an important role along with model development.
Robust fetoscopic mosaicking from deep learned flow fields
Authors: Alabi Oluwatosin , Bano Sophia , Vasconcelos Francisco , David Anna L. , Deprest Jan , Stoyanov Danail 
Published: May 2022

Abstract
Purpose
Fetoscopic laser photocoagulation is a minimally invasive procedure to treat twin-to-twin transfusion syndrome during pregnancy by stopping irregular blood flow in the placenta. Building an image mosaic of the placenta and its network of vessels could assist surgeons to navigate in the challenging fetoscopic environment during the procedure.

Methodology
We propose a fetoscopic mosaicking approach by combining deep learning-based optical flow with robust estimation for filtering inconsistent motions that occurs due to floating particles and specularities. While the current state of the art for fetoscopic mosaicking relies on clearly visible vessels for registration, our approach overcomes this limitation by considering the motion of all consistent pixels within consecutive frames. We also overcome the challenges in applying off-the-shelf optical flow to fetoscopic mosaicking through the use of robust estimation and local refinement.

Results
We compare our proposed method against the state-of-the-art vessel-based and optical flow-based image registration methods, and robust estimation alternatives. We also compare our proposed pipeline using different optical flow and robust estimation alternatives.

Conclusions
Through analysis of our results, we show that our method outperforms both the vessel-based state of the art and LK, noticeably when vessels are either poorly visible or too thin to be reliably identified. Our approach is thus able to build consistent placental vessel mosaics in challenging cases where currently available alternatives fail.
Dreams and nightmares during the pandemic
Authors: Ableidinger Severin , Nierwetberg Franziska , Holzinger Brigitte 
Published: May 2022

AbstractThe pandemic caused by the coronavirus disease 2019 (COVID-19) had a huge impact on public mental health. This was also reflected in dreams. Not only did people start to remember more dreams, but dream content changed as themes like sickness, confinement, and—in the English-speaking world—even bugs began to dominate. This also led to an increase in nightmare frequency. There are various factors that contributed to this change in the dream landscape. Some people have started to sleep more and hereby spend more time in REM sleep, which is known to increase dream recall and further lead to bizarre and vivid dreams. On the other hand, stress and poor mental health had an impact on sleep, and sleep quality thus dropped in many individuals. Poor sleep quality can also lead to an increase in dream recall. Dreams are known to regulate mood, so the rise in dreams and the change in dream content could also reflect a reaction to the overall rise in stress and decline in mental health. Recent studies have shown that as the pandemic progresses, further changes in mental health, dream recall, and dream content arise, but data are still scarce. Further research could help understand the impact the pandemic still has on mental health and dreams, and how this impact is changing over the course of the pandemic.
Encouraging research on recursive thinking through the lens of a model of the spread of contagious diseases
Authors: Sandefur James , Manaster Alfred B. 
Published: May 2022

AbstractRecursive reasoning is a powerful tool used extensively in problem solving. For us, recursive reasoning includes iteration, sequences, difference equations, discrete dynamical systems, pattern identification, and mathematical induction; all of these can represent how things change, but in discrete jumps. Given the school mathematics curriculum’s later emphasis on calculus—the mathematics of change in continuous contexts—it is surprising that the curriculum seems to neglect recursive thinking after the early grades. Research shows that recursion supports the learning of algebra among younger students, but the lack of similar research with older students is concerning. In this paper we suggest possible affordances from teaching recursive modeling, including a basic model of the spread of contagious diseases. We also discuss different ways to present these models at various points in the curriculum that might develop connections between mathematics and the real world, and support students’ learning of mathematics. This leads to what we, as mathematicians, think would be interesting research questions for mathematical educators.
Differentiation Epitopes Define Hematopoietic Stem Cells and Change with Cell Cycle Passage
Authors: Goldberg Laura R. , Dooner Mark S. , Papa Elaine , Pereira Mandy , Del Tatto Michael , Cheng Yan , Wen Sicheng , Quesenberry Peter J. 
Published: May 2022

AbstractHematopoietic stem cells express differentiation markers B220 and Gr1 and are proliferative. We have shown that the expression of these entities changes with cell cycle passage. Overall, we conclude that primitive hematopoietic stem cells alter their differentiation potential with cell cycle progression.
Graphical Abstract
Murine derived long-term hematopoietic stem cells (LT-HSC) are cycling and thus always changing phenotype. Here we show that over one half of marrow LT-HSC are in the population expressing differentiation epitopes and that B220 and Gr-1 positive populations are replete with LT-HSC after a single FACS separation but if subjected to a second separation these cells no longer contain LT-HSC. However, with second separated cells there is a population appearing that is B220 negative and replete with cycling c-Kit, Sca-1 CD150 positive LT-HSC. There is a 3–4 h interval between the first and second B220 or GR-1 FACS separation during which the stem cells continue to cycle. Thus, the LT-HSC have lost B220 or GR-1 expression as the cells progress through cell cycle, although they have maintained the c-kit, Sca-1 and CD150 stem cells markers over this time interval. These data indicate that cycling stem cells express differentiation epitopes and alter their differentiation potential with cell cycle passage.
The 16th-19th Century Soundtoll Registers Online: Uncovering Traded Plant Diversity between the North and the Baltic Seas
Authors: De Groot W. , Van Andel T. , Kool A. , Hazenberg M. , Kjesrud K. , Teixidor-Toneu I. 
Published: May 2022

AbstractStudies of European trade have largely focused on bulk commodities, ignoring minor products. The Danish Soundtoll Registers Online (STRO) document the North-Baltic Seas maritime trade from the 16th century to the 19th. They are an untapped resource to understand the trade of plant products. Here, we present an overview of plants recorded in the STRO from 1497–1857, based on thousands of handwritten vernacular plant name variations in Danish. We found 264 plant products corresponding to 140 botanical taxa. We confirm previous findings regarding bulk goods, such as wood, wine, and (sub)tropical spices, but also uncover trade of wild food plants and herbal medicines. Notably dodder (Cuscuta spp.) and purging cassia (Cassia fistula L.) were traded as frequently as currently well-known plant-based commodities such as tea (Camellia sinensis [L.] Kuntze) and rhubarb (Rheum rhabarbarum L.). This indicates their former importance. Through the botanically identified dataset we present here, the STRO reveal the diversity of historical plant trade. We discuss what this overview adds to the understanding of historic plant trade in Europe and outline suggestions for future research that can be addressed using these data.
The Impact of the Covid-19 Pandemic on Iranian Oil and Gas Industry Planning: A Survey of Business Continuity Challenges
Authors: Razavi Seyyed Abdollah , Asgary Ali , Khaleghi Marjan 
Published: May 2022

AbstractThe Covid-19 pandemic has severely affected various aspects of life, and its compounding and cascading impacts have been observed in most industries and firms. The oil and gas (O&G) industry was among the first to experience the impacts as the pandemic began due to the global economic recession and a sharp decline in demand for oil. The pandemic revealed major risk management and business continuity challenges and uncovered some of the vulnerabilities of the O&G industry and its major companies during a prolonged global disaster. Examining and understanding how the Covid-19 pandemic impacted the O&G sector in different countries, considering their unique circumstances, can provide important lessons for managing the current and future similar events. This study investigated various impacts of the Covid-19 pandemic on the O&G industry using Iran’s Pars Oil and Gas Company (POGC) as a case study. Data were collected through in-depth interviews with key managers of the company. Qualitative methods, specifically thematic analysis, were used to analyze the data. Findings of this study provide further insights into how the pandemic impacted the operations, risks, and business continuity of the POCG. The results show that the pandemic caused significant operational, financial, and legal impacts by disrupting routine maintenance, reducing the availability of human resources under the public health measures and mobility restrictions, increasing processing and delivery times, increasing costs and decreasing revenues, and delaying contractual obligations.
Evolution of the Chinese Intellectual Property Rights System: IPR Law Revisions and Enforcement
Authors: Hong Jie , Edler Jakob , Massini Silvia 
Published: May 2022

ABSTRACTSince the first Trademark Law was enacted in China in 1982, the Chinese intellectual property rights (IPR) system has undergone significant changes in both the design of the legislation and its enforcement. In this article, we analyze the evolution of IPR legislation and enforcement in China. To this end, we illustrate the evolutionary changes of the Chinese IPR system and analyze the changes introduced in four revisions (1992–1993, 2000–2001, 2008–2013, and 2019–2020). Our analysis shows that Patent Law, Trademark Law, and Copyright Law have been substantially enhanced, especially since 2000, when China improved its IPR system to comply with the TRIPS Agreement and join the WTO, and especially the most recent amendments of these three IP Laws. We discuss the number of IPR infringement cases handled by both relevant administrative authorities and courts to analyze IPR enforcement in China. Results indicate that the development of IPR protection enforcement followed the improvement of relevant IPR laws. The two revisions introduced after 2008, changes in the Chinese IPR system, and an increasing number of IPR infringement cases handled by relevant authorities also suggest the willingness of the Chinese government to further enhance its IPR protection.
Magical thinking in individuals with high polygenic risk for schizophrenia but no non-affective psychoses—a general population study
Authors: Saarinen Aino , Lyytikäinen Leo-Pekka , Hietala Jarmo , Dobewall Henrik , Lavonius Veikka , Raitakari Olli , Kähönen Mika , Sormunen Elina , Lehtimäki Terho , Keltikangas-Järvinen Liisa 
Published: May 2022

AbstractA strong genetic background for psychoses is well-established. Most individuals with a high genetic risk for schizophrenia, however, do not develop the disorder. We investigated whether individuals, who have a high genetic risk for schizophrenia but no non-affective psychotic disorders, are predisposed to develop milder forms of deviant thinking in terms of magical thinking. Participants came from the population-based Young Finns Study (n = 1292). The polygenic risk score for schizophrenia (PRS) was calculated on the basis of the most recent genome-wide association study (GWAS). Psychiatric diagnoses over the lifespan were collected up to 2017 from the registry of hospital care. Magical thinking was evaluated with the Spiritual Acceptance Scale (e.g., beliefs in telepathy, miracles, mystical events, or sixth sense) of the Temperament and Character Inventory in 1997, 2001, and 2012 (participants were 20–50-year-olds). We found that, among those who did not develop non-affective psychotic disorders, high PRS predicted higher magical thinking in adulthood (p = 0.001). Further, PRS predicted different developmental courses: a low PRS predicted a steady decrease in magical thinking from age 20 to 50 years, while in individuals with high PRS the decrease in magical thinking ceased in middle age so that their level of magical thinking remained higher than expected for that age. These findings remained when controlling for sex, childhood family environment, and adulthood socioeconomic factors. In conclusion, if high PRS does not lead to a non-affective psychotic disorder, it predicts milder forms of deviant thinking such as elevated magical thinking in adulthood, especially in middle age. The finding enhances our understanding of different outcomes of high genetic psychosis risk.
How should we report the foveal status in eyes with “macula-off” retinal detachment?
Authors: Klaas Julian E. , Siedlecki Jakob , Steel David H. , Laidlaw D. Alistair H. , Priglinger Siegfried 
Published: May 2022

AbstractWhilst pre- and postoperative multimodal imaging technologies including optical coherence tomography (OCT) have investigated the morphological correlates of worsened visual outcomes in rhegmatogenous retinal detachment (RRD) with foveal involvement, the nomenclature has adhered to the traditional ophthalmoscopy-based and rather vague term “macula-off”. This article appraises the current literature with regard to the preoperative assessment and nomenclature of the foveal status in macula involving retinal detachment (MIRD). A literature review of recent publications assessing functional or morphological outcomes in MIRD was conducted, using the search terms “fovea-off” or “macula-off”. The search date was April 28th, 2021. Original studies in English language were included. Case reports, review articles or letters were excluded. Forty relevant articles (range of publication dates: July 29th, 2020 - April 18th, 2021) were reviewed to assess the diagnostic modalities used, morphological parameters assessed, and any specific nomenclature introduced to specify the extent of macular detachment. The results suggest widespread variability and inconsistencies with regard to the preoperative assessment, diagnostic modalities and nomenclature used to describe the foveal status in eyes with RRD termed “macula-off”. The extent of macular detachment may be classified by a wide range of morphological parameters, including the height of foveal detachment and the ETDRS grid as overlay tool in OCT devices. There is a scientific and clinical need for an updated nomenclature for eyes with “macula-off” RRD. Preoperative OCT findings should be reported on a regular and standardized basis in order to establish a consensus how to report the foveal status in eyes with MIRD.
Tracking perovskite crystallization via deep learning-based feature detection on 2D X-ray scattering data
Authors: Starostin Vladimir , Munteanu Valentin , Greco Alessandro , Kneschaurek Ekaterina , Pleli Alina , Bertram Florian , Gerlach Alexander , Hinderhofer Alexander , Schreiber Frank 
Published: May 2022

AbstractUnderstanding the processes of perovskite crystallization is essential for improving the properties of organic solar cells. In situ real-time grazing-incidence X-ray diffraction (GIXD) is a key technique for this task, but it produces large amounts of data, frequently exceeding the capabilities of traditional data processing methods. We propose an automated pipeline for the analysis of GIXD images, based on the Faster Region-based Convolutional Network architecture for object detection, modified to conform to the specifics of the scattering data. The model exhibits high accuracy in detecting diffraction features on noisy patterns with various experimental artifacts. We demonstrate our method on real-time tracking of organic-inorganic perovskite structure crystallization and test it on two applications: 1. the automated phase identification and unit-cell determination of two coexisting phases of Ruddlesden–Popper 2D perovskites, and 2. the fast tracking of MAPbI3 perovskite formation. By design, our approach is equally suitable for other crystalline thin-film materials.
Timescale of a magmatic-hydrothermal system revealed by 40Ar–39Ar geochronology: the Mio-Pliocene Campiglia Marittima system (Tuscany, Italy)
Authors: Di Vincenzo Gianfranco , Vezzoni Simone , Dini Andrea , Rocchi Sergio 
Published: May 2022

AbstractPetrology and timing of magmatic-hydrothermal systems and the linkage between plutonic and volcanic domains are central topics in geosciences, because of broad implications for natural hazards and exploitation of natural resources. We investigated by the 40Ar–39Ar method the timescale of a well-characterized natural example, the Mio-Pliocene Campiglia Marittima magmatic-hydrothermal system (Tuscany, Italy). 40Ar–39Ar data from pristine and homogeneous trioctahedral micas and sanidine from the plutonic-hydrothermal-subvolcanic-volcanic sequence (from the Botro ai Marmi Granite to the San Vincenzo Rhyolite) record crystallization ages and define a temporal sequence lasting 973 ± 43 ka, starting from 5.409 ± 0.043 Ma. K-feldspar from mafic and felsic porphyries, unlike micas, are affected by submillimetre, micropore laden, alteration domains consisting of secondary K-feldspar and albite, and yielded staircase-shaped age spectra, compatible with a ternary mixing. Results document that the San Vincenzo Rhyolite consists of two diachronous batches, the first emplaced at 5.0024 ± 0.0062 Ma, closely following emplacement of mafic porphyries, the second at 4.4359 ± 0.0045 Ma. Bulk of hydrothermal deposits, consisting of skarns and associated Zn–Pb(-Ag) mineralization predating Fe–Cu ore, formed within the first ~ 400-ka lifetime of the whole sequence and was closely followed by the first eruption which should have run out most of the ore-forming potential of the system.
Interpretability and fairness evaluation of deep learning models on MIMIC-IV dataset
Authors: Meng Chuizheng , Trinh Loc , Xu Nan , Enouen James , Liu Yan 
Published: May 2022

AbstractThe recent release of large-scale healthcare datasets has greatly propelled the research of data-driven deep learning models for healthcare applications. However, due to the nature of such deep black-boxed models, concerns about interpretability, fairness, and biases in healthcare scenarios where human lives are at stake call for a careful and thorough examination of both datasets and models. In this work, we focus on MIMIC-IV (Medical Information Mart for Intensive Care, version IV), the largest publicly available healthcare dataset, and conduct comprehensive analyses of interpretability as well as dataset representation bias and prediction fairness of deep learning models for in-hospital mortality prediction. First, we analyze the interpretability of deep learning mortality prediction models and observe that (1) the best-performing interpretability method successfully identifies critical features for mortality prediction on various prediction models as well as recognizing new important features that domain knowledge does not consider; (2) prediction models rely on demographic features, raising concerns in fairness. Therefore, we then evaluate the fairness of models and do observe the unfairness: (1) there exists disparate treatment in prescribing mechanical ventilation among patient groups across ethnicity, gender and age; (2) models often rely on racial attributes unequally across subgroups to generate their predictions. We further draw concrete connections between interpretability methods and fairness metrics by showing how feature importance from interpretability methods can be beneficial in quantifying potential disparities in mortality predictors. Our analysis demonstrates that the prediction performance is not the only factor to consider when evaluating models for healthcare applications, since high prediction performance might be the result of unfair utilization of demographic features. Our findings suggest that future research in AI models for healthcare applications can benefit from utilizing the analysis workflow of interpretability and fairness as well as verifying if models achieve superior performance at the cost of introducing bias.