bluuebunny/crossref_metadata_2025_split huggingface dataset:
Large genomic introgression blocks of Phaseolus parvifolius Freytag bean into the common bean enhance the crossability between tepary and common beans
Authors: Barrera Santos , Berny Mier y Teran Jorge C. , Lobaton Juan David , Escobar Roosevelt , Gepts Paul , Beebe Steve , Urrea Carlos A. 
Published: December 2022

AbstractThe production of the common bean (Phaseolus vulgaris L.), one of the most important sources of protein and minerals and one of the most consumed grain legumes globally, is highly affected by heat and drought constraints. In contrast, the tepary bean (Phaseolus acutifolius A. Gray), a common bean‐related species, is adapted to hot and dry climates. Hybridization to introduce complex traits from the tepary bean into the common bean has been challenging, as embryo rescue is required. In this study, we report three novel interspecific lines that were obtained by crossing lines from prior common bean × tepary bean hybridization with Phaseolus parvifolius Freytag in order to increase the male gametic diversity to facilitate interspecific crosses. These interspecific lines enhanced the crossability of the common bean and tepary bean species while avoiding the embryo rescue process. Crossing these three interspecific lines with tepary beans resulted in 12‐fold more hybrid plants than crossing traditional common beans with tepary beans. Whole‐genome sequencing analysis of these three interspecific lines shows large introgressions of genomic regions corresponding to P. parvifolius on chromosomes that presumably contribute to reproductive barriers between both species. The development of these lines opens up the possibility of increasing the introgression of desirable tepary bean traits into the common bean to address constraints driven by climate change.
Gastrointestinal factors associated with risk of bronchiectasis in children
Authors: Duncan Daniel R. , Cohen Alexandra , Golden Clare , Lurie Margot , Mitchell Paul D. , Liu Enju , Simoneau Tregony , Rosen Rachel L. 
Published: December 2022

AbstractObjectiveTo evaluate gastrointestinal (GI) risk factors for bronchiectasis in children. We hypothesized that upper GI tract dysmotility would be associated with increased risk of bronchiectasis.Study designSubjects in this retrospective cohort study included those evaluated for persistent pulmonary symptoms in the Aerodigestive Center at Boston Children's Hospital who underwent chest computed tomography (CT) between 2002 and 2019. To determine gastrointestinal predictors of bronchiectasis, baseline characteristics, comorbidities, enteral tube status, medications received, gastroesophageal reflux burden, adequacy of swallow function, esophageal dysmotility, gastric dysmotility, and neutrophil count on bronchoalveolar lavage (BAL) were compared between patients with and without bronchiectasis. Proportions were compared with Fisher's exact test and binary logistic regression with stepwise selection was used for multivariate analysis. ROC analyses were utilized to compare BAL neutrophils and bronchiectasis.ResultsOf 192 subjects, 24% were found to have evidence of bronchiectasis on chest CT at age 7.9 ± 0.5 years. Enteral tubes (OR 5.77, 95% CI 2.25–14.83,p < 0.001) and increased BAL neutrophil count (OR 5.79, 95% CI 1.87–17.94,p = 0.002) were associated with increased risk while neurologic comorbidities were associated with decreased risk (OR 0.24, 95% CI 0.09–0.66,p = 0.006). Gastroesophageal reflux was not found to be a significant risk factor. Neutrophil counts >10% had 72% sensitivity and 60% specificity for identifying bronchiectasis.ConclusionsEnteral tubes were associated with significantly increased risk of bronchiectasis but gastroesophageal reflux was not. Providers should consider obtaining chest CT to evaluate for bronchiectasis in children found to have unexplained elevated BAL neutrophil count.
Utilization of the Critic Subnetwork of a Generative Adversarial Network as Detector of Morphological Material Change in Image Data
Authors: Beste Ariana , Bolintineanu Dan S. , Bufford Daniel C. 
Published: December 2022

AbstractThe resolution of computed tomography (CT) has become high enough to monitor morphological changes due to aging in materials in long‐term applications. We explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN‐generated images reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect; but both critic and morphological metrics analysis showed image differentiation.
Metal‐binding and circular permutation‐dependent thermodynamic and kinetic stability of azurin
Authors: Das Debanjana , Yadav Priya , Mitra Soumyajit , Ainavarapu Sri Rama Koti 
Published: December 2022

AbstractNative topology is known to determine the folding kinetics and the energy landscape of proteins. Furthermore, the circular permutation (CP) of proteins alters the order of the secondary structure connectivity while retaining the three‐dimensional structure, making it an elegant and powerful approach to altering native topology. Previous studies elucidated the influence of CP in proteins with different folds such as Greek key β‐barrel, β‐sandwich, β‐α‐β, and all α‐Greek key. CP mainly affects the protein stability and unfolding kinetics, while folding kinetics remains mostly unaltered. However, the effect of CP on metalloproteins is yet to be elaborately studied. The active site of metalloproteins poses an additional complexity in studying protein folding. Here, we investigate a CP variant (cpN42) of azurin—in both metal‐free and metal‐bound (holo) forms. As observed earlier in other proteins, apo‐forms of wild‐type (WT) and cpN42 fold with similar rates. In contrast, zinc‐binding accelerates the folding of WT but decelerates the folding of cpN42. On zinc‐binding, the spontaneous folding rate of WT increases by >250 times that of cpN42, which is unprecedented and the highest for any CP to date. On the other hand, zinc‐binding reduces the spontaneous unfolding rate of cpN42 by ~100 times, making the WT and CP azurins unfold at similar rates. Our study demonstrates metal binding as a novel way to modulate the unfolding and folding rates of CPs compared to their WT counterparts. We hope our study increases the understanding of the effect of CP on the folding mechanism and energy landscape of metalloproteins.
A Bayesian method for safety signal detection in ongoing blinded randomised controlled trials
Authors: Brock Kristian , Chen Chen , Ho Shuyen , Fuller Greg , Woolfolk Jared , McShea Cindy , Penard Nils 
Published: December 2022

AbstractSponsors have a responsibility to minimise risk to participants in clinical studies through safety monitoring. The FDA Final Rule for IND Safety Reporting requires routine aggregate safety evaluation, including in ongoing blinded studies. We are interested in estimating the probability that the true adverse event rate in the experimental arm exceeds that in the control arm. We developed a Bayesian approach that specifies an informative meta‐analytic predictive prior on the event probability in the control arm and an uninformative prior on that in the experimental arm. We combined these priors with a mixture likelihood that considers each patient in the ongoing blinded study may belong to the experimental or control arm. This allowed us to estimate the quantity of interest without unblinding. We evaluated our method by simulation, pairing scenarios that differed only in whether a safety signal was present or missing, and quantifying the ability of our model to discriminate using signal detection theory. Our approach shows benefit. It detects safety signals more reliably with greater sample sizes and for common rather than rare events. Performance does not deteriorate markedly when historical studies exhibit heterogeneous hazards or non‐constant hazards. Our method will allow us to monitor safety signals in ongoing blinded studies with the goal of earlier identification and risk mitigation. Our method could be adapted to use informative priors on both arms or predictive covariates where pertinent data exist. We stress that ongoing safety monitoring should involve a multi‐disciplinary team where statistical methods are paired with medical judgement.
“I Don't Like Peas!”: Using Picturebooks to Think Differently & Critically about Curriculum, Teaching, Learning, and Technology
Authors: Bintz William P. 
Published: December 2022

AbstractThis article shares a variety of picturebooks that invite teachers to think critically about curriculum, teaching, learning, and technology (CTLT). It posits that teaching and learning are not perfectible absolutes but continuous processes that invite teachers to develop beyond what they already know. Reading professional literature, conducting research, attending conferences, collaborating with colleagues, and discussing and reflecting on current practices are resources for teachers to grow and develop, instructionally and intellectually. Picturebooks are also important resources. Like all texts, picturebooks can offer meaning potentials that invite teachers to think critically about CTLT, as well as help K‐12 students and teachers develop a love affair with books.
A synthesis of ecosystem metabolism of China's major rivers and coastal zones (2000–2020)
Authors: Zhang Meng , Francis Robert A. , Chadwick Michael A. 
Published: December 2022

AbstractEcosystem metabolism is a vital measurement for understanding the dynamics of aquatic environments. China has a range of aquatic resources and in the past two decades, there has been an increasing interest in ecosystem metabolism research. However, no studies have evaluated overall variation and environmental patterns which affect metabolism in China's vast range of aquatic systems. For this paper, we searched for articles with metabolism data for China's major rivers and coastal zones from 2000 to 2020. We identified 127 studies documenting ecosystem metabolism functions including primary production (PP), community respiration (CR) and net ecosystem production (NEP). Using path analysis, we documented relationships across a range of environmental parameters. Light availability affected riverine and coastal PP (<0.1–10.7 gC m−2 day−1), while riverine PP was also linked to precipitation, photosynthesis‐related biomass, and land‐use variables. Riverine and coastal CR ranged from 0.01 to 24.3 gC m−2 day−1 and was affected strongly by nutrient concentrations. Average NEP ranged from 2.9 to 9.2 gC m−2 day−1, suggesting the potential of some of the evaluated ecosystems to be CO2 sinks. Within this review, the large spatiotemporal range allows for a wide‐ranging understanding of the variation of metabolic processes which contribute to CO2 dynamics and the role of aquatic ecosystems in regional climate change. Additionally, by evaluating aquatic ecosystem metabolism across such a diverse range of environmental conditions this work provides a scientific basis for future assessments of ecological risks under the complex conditions of climate change.This article is categorized under:
Science of Water > Water Quality
Science of Water > Water and Environmental Change
Water and Life > Nature of Freshwater Ecosystems
Wind plant power maximization via extremum seeking yaw control: A wind tunnel experiment
Authors: Kumar Devesh , Rotea Mario A. , Aju Emmanuvel J. , Jin Yaqing 
Published: December 2022

AbstractThis work describes the results from wind tunnel experiments performed to maximize wind plant total power output using wake steering via closed loop yaw angle control. The experimental wind plant consists of nine turbines arranged in two different layouts; both are two dimensional arrays and differ in the positioning of the individual turbines. Two algorithms are implemented to maximize wind plant power: Log‐of‐Power Extremum Seeking Control (LP‐ESC) and Log‐of‐Power Proportional Integral Extremum Seeking Control (LP‐PIESC). These algorithms command the yaw angles of the turbines in the upstream row. The results demonstrate that the algorithms can find the optimal yaw angles that maximize total power output. The LP‐PIESC reached the optimal yaw angles much faster than the LP‐ESC. The sensitivity of the LP‐PIESC to variations in free stream wind speed and initial yaw angles is studied to demonstrate robustness to variations in wind speed and unknown yaw misalignment.
Overcoming Abstraction: Affectual States in the Efforts to Decarbonize Energy Among Young Climate Activists in Stavanger, Norway
Authors: Lautrup Andy 
Published: December 2022

AbstractLautrup engages ethnographically with energy transitions towards a low-carbon future as experienced by young climate activists in Norway’s oil-capital Stavanger. By relating the activists’ sense of climate change as abstract to climate change’s manifestation in digital data models as a phenomenon taking place in no specific location and mainly in the future (Knox. 2021. “Hacking Anthropology”.Journal of the Royal Anthropological Institute27.S1 (2021): 108–126), the chapter shows that the activists work to overcome abstractions by focusing on the local and contemporary through examples that come from the Global North and provide visceral, embodied effects. The young activists’ concretizing practices, Lautrup argues, result in affective states that render concreteness as something desirable and abstraction as something undesirable to be overcome, but also that in an oil-city, there is a limit to the desirability of concreteness.
Mediatised Practices: Renovating Homes with Media and ICTs in Australia
Authors: Aggeli Aggeliki , Mechlenborg Mette 
Published: December 2022

AbstractThe extensive use of media and information and communication technologies (ICTs) in the household is building a new normality, where the use of technology is imperceptible to its users. Within this context, home renovation can be examined as a mediatised practice, which suggests the interactive transformation of practices which takes place with and through media. Our chapter is based on an interdisciplinary Australian study of 13 home renovations and their media practices. In this chapter, we argue that home renovation activities have moved into the digital realm. Furthermore, we emphasise that these mediatised home renovation practices contribute to the development of new mediatised domains that could assist in the transition and domestication of low-carbon practices and technologies.
Deep Learning for the Benes Filter
Authors: Lobbe Alexander 
Published: December 2022

AbstractThe filtering problem is concerned with the optimal estimation of a hidden state given partial and noisy observations. Filtering is extensively studied in the theoretical and applied mathematical literature. One of the central challenges in filtering today is the numerical approximation of the optimal filter. Here, accurate and fast methods are actively sought after, especially for such high-dimensional settings as numerical weather prediction, for example. In this paper we present a brief study of a new numerical method based on the mesh-free neural network representation of the density of the solution of the filtering problem achieved by deep learning. Based on the classical SPDE splitting method, our algorithm includes a recursive normalisation procedure to recover the normalised conditional distribution of the signal process. The present work uses the Benes model as a benchmark. The Benes filter is a well-known continuous-time stochastic filtering model in one dimension that has the advantage of being explicitly solvable. Within the analytically tractable setting of the Benes filter, we discuss the role of nonlinearity in the filtering model equations for the choice of the domain of the neural network. Further, we present the first study of the neural network method with an adaptive domain for the Benes model.
A Two-Step Numerical Scheme in Time for Surface Quasi Geostrophic Equations Under Location Uncertainty
Authors: Fiorini Camilla , Boulvard Pierre-Marie , Li Long , Mémin Etienne 
Published: December 2022

AbstractIn this work we consider the surface quasi-geostrophic (SQG) system under location uncertainty (LU) and propose a Milstein-type scheme for these equations, which is then used in a multi-step method. The SQG system considered here consists of one stochastic partial differential equation, which models the stochastic transport of the buoyancy, and a linear operator linking the velocity and the buoyancy. In the LU setting, the Euler-Maruyama scheme converges with weak order 1 and strong order 0.5. Our aim is to develop higher order schemes in time, based on a Milstein-type scheme in a multi-step framework. First we compared different kinds of Milstein schemes. The scheme with the best performance is then included in the two-step scheme. Finally, we show how our two-step scheme decreases the error in comparison to other multi-step schemes.
Feedbackorientierte Lernumgebungen zur Gestaltung offener Aufgabenstellungen mit Machine Learning, AR und 3D-Druck
Authors: Lutz Tim 
Published: December 2022

ZusammenfassungDieser Artikel beschäftigt sich mit verschiedenen Ansätzen der Entwicklung feedbackorientierter Lernumgebungen zur Gestaltung immer offener gefasster Aufgabenstellungen mit Machine Learning (ML), Augmented Reality und 3D-Druck. Vom Begriff „Feedback“ ausgehend werden Aspekte des computerbasierten Feedbacks dargestellt. Dabei wird die in der Hochschulmathematik sehr beliebte Software STACK als ein aktuelles Beispiel für vielfältige Feedbackmöglichkeiten aufgezeigt. Die konkrete Ausgestaltung von computerbasiertem Feedback mittels STACK führt dann zu Überlegungen, wie Feedback für noch „offenere“ Aufgabenstellungen designt werden kann. Der Hauptteil dieses Artikels zeigt dies an Praxisbeispielen. Für die Mathematikdidaktik sollen Bereiche ausgelotet werden, um vielfältige neue digital gestützte Feedbackansätze zu entwickeln.
Cardiac MRI in patients with COVID-19 infection
Authors: Abdeldayem Emad H. , Raief Mosaad Basant M. , Yassin Aya , Abdelrahman Ahmed S. 
Published: December 2022

Abstract
Objective
COVID-19 infection is a systemic disease with various cardiovascular symptoms and complications. Cardiac MRI with late gadolinium enhancement is the modality of choice for the assessment of myocardial involvement. T1 and T2 mapping can increase diagnostic accuracy and improve further management. Our study aimed to evaluate the different aspects of myocardial damage in cases of COVID-19 infection using cardiac MRI.

Methods
This descriptive retrospective study included 86 cases, with a history of COVID-19 infection confirmed by positive RT-PCR, who met the inclusion criteria. Patients had progressive chest pain or dyspnoea with a suspected underlying cardiac cause, either by an abnormal electrocardiogram or elevated troponin levels. Cardiac MRI was performed with late contrast-enhanced (LGE) imaging, followed by T1 and T2 mapping.

Results
Twenty-four patients have elevated hsTnT with a median hsTnT value of 133 ng/L (IQR: 102 to 159 ng/L); normal value < 14 ng/L. Other sixty-two patients showed elevated hsTnI with a median hsTnI value of 1637 ng/L (IQR: 1340 to 2540 ng/L); normal value < 40 ng/L. CMR showed 52 patients with acute myocarditis, 23 with Takotsubo cardiomyopathy, and 11 with myocardial infarction. Invasive coronary angiography was performed only in selected patients.

Conclusion
Different COVID-19-related cardiac injuries may cause similar clinical symptoms. Cardiac MRI is the modality of choice to differentiate between the different types of myocardial injury such as Takotsubo cardiomyopathy and infection-related cardiomyopathy or even acute coronary syndrome secondary to vasculitis or oxygen-demand mismatch.

Key Points
• It is essential to detect early COVID-related cardiac injury using different cardiac biomarkers and cardiac imaging, as it has a significant impact on patient management and outcome.
• Cardiac MRI is the modality of choice to differentiate between the different aspects of COVID-related myocardial injury.
Mushroom to manoeuvre? Using photogrammetry to track the movement and survival of free-living corals
Authors: Bayley D. T. I. , Mogg A. O. M. 
Published: December 2022

AbstractMushroom corals can play an important role in tropical reef ecosystems by providing habitat and performing important ecological functions. Unlike most stony corals, free-living mushroom corals can move, both passively and actively, and can use this ability to escape competition or harmful environments. However, as their movement is typically slow, occurs over relatively small scales, and is traditionally hard to measure, their movement ecology is little researched. Nevertheless, quantitative geospatial data on species’ movement, distribution, survival, and interaction can improve mechanistic modelling of community dynamics in various environments. We use ‘structure from motion’ photogrammetry to track 51 individual corals’ 3D movement and survival over one year within an isolated and enclosed lagoon. This technique essentially provides a large-scale quantitative community time-lapse and allows detailed individual level life-history data to be collected over spatial and temporal scales that were previously impractical.
Oral and general health conditions involved in periodontal status during pregnancy: a prospective cohort study
Authors: Gil-Montoya J. A. , Rivero-Blanco T. , Leon-Rios X. , Exposito-Ruiz M. , Pérez-Castillo I. , Aguilar-Cordero M. J. 
Published: December 2022

Abstract
Purpose
Pregnancy is a period in a woman’s life that has important consequences on oral health, particularly for gingival health. Present study aims to identify women at higher risk of developing periodontal disease (gingivitis and periodontitis) during late pregnancy and evaluate how this condition evolves during this period.

Methods
Prospective cohort study was designed with pregnant women who were assessed during the first and third trimesters of gestation in a southern Spanish public hospital. Data regarding gingival and periodontal health, oral hygiene, and overall health status (obesity and diabetes mellitus) were collected. Reporting followed STROBE checklist.

Results
Significantly higher number of women had the periodontal and gingival disease in the third trimester of gestation compared with in early pregnancy. In the third trimester of gestation, 42 (28.6%) and 63 (42.9%) of women presented symptoms of periodontal disease and gingival disease, respectively. Obesity (OR 2.834; 95%CI 0.919–8.741), worse oral hygiene during the first trimester of gestation (OR: 4.031; 95%CI 2.12–7.65), and periodontal disease during early pregnancy (OR: 15.104; 95%CI 3.60–63.36) most effectively predicted periodontal disease during late pregnancy.

Conclusions
Pregnancy is associated with exacerbated periodontal and gingival disease symptoms throughout the different trimesters of gestation. Obesity and oral hygiene during early pregnancy were the risk factors that most contributed to the aforementioned changes in periodontal disease.