bluuebunny/crossref_metadata_2025_split huggingface dataset:
Global perspective of environmental distribution and diversity of Perkinsea (Alveolata) explored by a meta-analysis of eDNA surveys
Authors: Metz Sebastian , Itoïz Sarah , Obiol Aleix , Derelle Evelyne , Massana Ramon , Berney Cédric , de Vargas Colomban , Soudant Philippe , Monier Adam , Chambouvet Aurélie 
Published: November 2023

AbstractPerkinsea constitutes a lineage within the Alveolata eukaryotic superphylum, mainly composed of parasitic organisms. Some described species represent significant ecological and economic threats due to their invasive ability and pathogenicity, which can lead to mortality events. However, the genetic diversity of these described species is just the tip of the iceberg. Environmental surveys targeting this lineage are still scarce and mainly limited to the Northern Hemisphere. Here, we aim to conduct an in depth exploration of the Perkinsea group, uncovering the diversity across a variety of environments, including those beyond freshwater and marine ecosystems. We seek to identify and describe putative novel organisms based on their genetic signatures. In this study, we conducted an extensive analysis of a metabarcoding dataset, focusing on the V4 region of the 18S rRNA gene (the EukBank dataset), to investigate the diversity, distribution and environmental preferences of the Perkinsea. Our results reveal a remarkable diversity within the Perkinsea, with 1568 Amplicon Sequence Variants (ASVs) identified across thousands of environmental samples. Surprisingly, we showed a substantial diversity of Perkinsea within soil samples (269 ASVs), challenging the previous assumption that this group is confined to marine and freshwater environments. In addition, we revealed that a notable proportion of Perkinsea ASVs (428 ASVs) could correspond to putative new organisms, encompassing the well-established taxonomic group Perkinsidae. Finally, our study shed light on previously unveiled taxonomic groups, including the Xcellidae, and revealed their environmental distribution. These findings demonstrate that Perkinsea exhibits far greater diversity than previously detected and surprisingly extends beyond marine and freshwater environments. The meta-analysis conducted in this study has unveiled the existence of previously unknown clusters within the Perkinsea lineage, solely identified based on their genetic signatures. Considering the ecological and economic importance of described Perkinsea species, these results suggest that Perkinsea may play a significant, yet previously unrecognized, role across a wide range of environments, spanning from soil environments to the abyssal zone of the open ocean with important implications for ecosystem functioning.
Unveiling the influence of task-relevance of emotional faces on behavioral reactions in a multi-face context using a novel Flanker-Go/No-go task
Authors: Montalti Martina , Mirabella Giovanni 
Published: November 2023

AbstractRecent research indicates that emotional faces affect motor control only when task-relevant. However, these studies utilized a single-face presentation, which does not accurately mirror real-life situations wherein we frequently engage with multiple individuals simultaneously. To overcome this limitation, we gave 40 participants two versions of a novel Flanker-Go/No-go task, where we presented three-face stimuli with a central target and two task-irrelevant flankers that could be congruent or incongruent with the target for valence and gender. In the Emotional Discrimination Task (EDT), participants had to respond to fearful or happy targets and refrain from moving with neutral ones. In the Gender Discrimination Task (GDT), the same images were shown, but participants had to respond according to the target's gender. In line with previous studies, we found an effect of valence only in EDT, where fearful targets increased reaction times and omission error rates compared to happy faces. Notably, the flanker effect, i.e., slower and less accurate responses in incongruent than congruent conditions, was not found. This likely stems from the higher perceptual complexity of faces than that of stimuli traditionally used in the Eriksen Flanker task (letters or signs), leading to a capacity limit in face feature processing.
Simulation study of a novel small animal FLASH irradiator (SAFI) with integrated inverse-geometry CT based on circularly distributed kV X-ray sources
Authors: Tan Yuewen , Zhou Shuang , Haefner Jonathan , Chen Qinghao , Mazur Thomas R. , Darafsheh Arash , Zhang Tiezhi 
Published: November 2023

AbstractUltra-high dose rate (UHDR) radiotherapy (RT) or FLASH-RT can potentially reduce normal tissue toxicity. A small animal irradiator that can deliver FLASH-RT treatments similar to clinical RT treatments is needed for pre-clinical studies of FLASH-RT. We designed and simulated a novel small animal FLASH irradiator (SAFI) based on distributed x-ray source technology. The SAFI system comprises a distributed x-ray source with 51 focal spots equally distributed on a 20 cm diameter ring, which are used for both FLASH-RT and onboard micro-CT imaging. Monte Carlo simulation was performed to estimate the dosimetric characteristics of the SAFI treatment beams. The maximum dose rate, which is limited by the power density of the tungsten target, was estimated based on finite-element analysis (FEA). The maximum DC electron beam current density is 2.6 mA/mm2, limited by the tungsten target's linear focal spot power density. At 160 kVp, 51 focal spots, each with a dimension of $$2\times 20$$

2
×
20

mm2 and 10° anode angle, can produce up to 120 Gy/s maximum DC irradiation at the center of a cylindrical water phantom. We further demonstrate forward and inverse FLASH-RT planning, as well as inverse-geometry micro-CT with circular source array imaging via numerical simulations.
Mock community experiments can inform on the reliability of eDNA metabarcoding data: a case study on marine phytoplankton
Authors: Marinchel Nadia , Marchesini Alexis , Nardi Davide , Girardi Matteo , Casabianca Silvia , Vernesi Cristiano , Penna Antonella 
Published: November 2023

AbstractEnvironmental DNA metabarcoding is increasingly implemented in biodiversity monitoring, including phytoplankton studies. Using 21 mock communities composed of seven unicellular diatom and dinoflagellate algae, assembled with different composition and abundance by controlling the number of cells, we tested the accuracy of an eDNA metabarcoding protocol in reconstructing patterns of alpha and beta diversity. This approach allowed us to directly evaluate both qualitative and quantitative metabarcoding estimates. Our results showed non-negligible rates (17–25%) of false negatives (i.e., failure to detect a taxon in a community where it was included), for three taxa. This led to a statistically significant underestimation of metabarcoding-derived alpha diversity (Wilcoxon p = 0.02), with the detected species richness being lower than expected (based on cell numbers) in 8/21 mock communities. Considering beta diversity, the correlation between metabarcoding-derived and expected community dissimilarities was significant but not strong (R2 = 0.41), indicating suboptimal accuracy of metabarcoding results. Average biovolume and rDNA gene copy number were estimated for the seven taxa, highlighting a potential, though not exhaustive, role of the latter in explaining the recorded biases. Our findings highlight the importance of mock communities for assessing the reliability of phytoplankton eDNA metabarcoding studies and identifying their limitations.
A pilot study on the efficacy of GPT-4 in providing orthopedic treatment recommendations from MRI reports
Authors: Truhn Daniel , Weber Christian D. , Braun Benedikt J. , Bressem Keno , Kather Jakob N. , Kuhl Christiane , Nebelung Sven 
Published: November 2023

AbstractLarge language models (LLMs) have shown potential in various applications, including clinical practice. However, their accuracy and utility in providing treatment recommendations for orthopedic conditions remain to be investigated. Thus, this pilot study aims to evaluate the validity of treatment recommendations generated by GPT-4 for common knee and shoulder orthopedic conditions using anonymized clinical MRI reports. A retrospective analysis was conducted using 20 anonymized clinical MRI reports, with varying severity and complexity. Treatment recommendations were elicited from GPT-4 and evaluated by two board-certified specialty-trained senior orthopedic surgeons. Their evaluation focused on semiquantitative gradings of accuracy and clinical utility and potential limitations of the LLM-generated recommendations. GPT-4 provided treatment recommendations for 20 patients (mean age, 50 years ± 19 [standard deviation]; 12 men) with acute and chronic knee and shoulder conditions. The LLM produced largely accurate and clinically useful recommendations. However, limited awareness of a patient’s overall situation, a tendency to incorrectly appreciate treatment urgency, and largely schematic and unspecific treatment recommendations were observed and may reduce its clinical usefulness. In conclusion, LLM-based treatment recommendations are largely adequate and not prone to ‘hallucinations’, yet inadequate in particular situations. Critical guidance by healthcare professionals is obligatory, and independent use by patients is discouraged, given the dependency on precise data input.
Inhibition of SARS-CoV-2 3CL protease by the anti-viral chimeric protein RetroMAD1
Authors: Chan Lee-Chin , Mat Yassim Aini Syahida , Ahmad Fuaad Abdullah Al Hadi , Leow Thean Chor , Sabri Suriana , Radin Yahaya Radin Shafierul , Abu Bakar Awang Muhammad Sagaf 
Published: November 2023

AbstractCOVID-19 results from SARS-CoV-2, which mutates frequently, challenging current treatments. Therefore, it is critical to develop new therapeutic drugs against this disease. This study explores the interaction between SARS-CoV-2 3CLpro and RetroMAD1, a well-characterized coronavirus protein and potential drug target, using in-silico methods. The analysis through the HDOCK server showed stable complex formation with a binding energy of -12.3, the lowest among reference drugs. The RetroMAD1-3CLpro complex underwent a 100 ns molecular dynamics simulation (MDS) in an explicit solvation system, generating various trajectories, including RMSD, RMSF, hydrogen bonding, radius of gyration, and ligand binding energy. MDS results confirmed intact interactions within the RetroMAD1-3CLpro complex during simulations. In vitro experiments validated RetroMAD1's ability to inhibit 3CLpro enzyme activity and prevent SARS-CoV-2 infection in human bronchial cells. RetroMAD1 exhibited antiviral efficacy comparable to Remdesivir without cytotoxicity at effective concentrations. These results suggest RetroMAD1 as a potential drug candidate against SARS-CoV-2, warranting further in vivo and clinical studies to assess its efficiency.
Stacking and spin order in a van der Waals Mott insulator 1T-TaS2
Authors: Park Jae Whan , Lee Jinwon , Yeom Han Woong 
Published: November 2023

AbstractQuasi-two-dimensional charge density wave system of 1T-TaS2 has attracted recent interest due to topological excitations, emergent superconductivity, ultrafast synaptic functionality, and the possibility of a quantum spin liquid state. While electron correlation has been known to be essential in this system, the nature of its insulating phase is currently under debate. Here, we reinvestigate the origin of the insulating band structures of the 1T-TaS2 surface using density-functional theory calculations to consider the recently-raised issues such as interlayer coupling, surface effect, and interlayer spin ordering. We identify four distinct electronic states of the surface layer such as a 2D Mott phase, a strongly-coupled antiferromagnetic insulator, a weakly-coupled ferromagnetic insulator, and a small-gap semiconductor, depending on types of the surface termination and the interlayer spin configuration. These distinct surface electronic states explain the different sizes of spectroscopic band gaps observed in scanning tunneling microscopy, revealing the complexity of the interlayer charge and spin couplings in layered correlated materials.
Skillful multiyear to decadal predictions of sea level in the North Atlantic Ocean and U.S. East Coast
Authors: Zhang Liping , Delworth Thomas L. , Yang Xiaosong , Zeng Fanrong 
Published: November 2023

AbstractLong-term sea-level rise and multiyear to decadal sea level variations pose substantial risks for flooding and erosion in coastal communities. Here we use observations and climate model predictions to show that sea level variations along the U.S. East Coast are skillfully predictable 3 to 10 years in advance. The most predictable component of sea level is a basin scale upward trend, predictable a decade in advance and primarily a response to increasing greenhouse gases. Significant additional predictability comes from multidecadal variations of the Atlantic Meridional Overturning Circulation (AMOC). While perfect model simulations show AMOC-related sea level predictability of 5-7 years, model biases and initialization uncertainties reduce the realized predictive skill to 3-5 years, depending on location. Overall, greenhouse gas warming and predictable AMOC variations lead to multiyear to decadal prediction skill for sea level along the U.S. East Coast. Such skill could have significant societal benefit for planning and adaptation.
Commentary on: Increased stiffness of omental arteries from late pregnant women at advanced maternal age
Authors: Stanhewicz Anna E. , Schwartz Kelsey S. , Lee Ruda 
Published: November 2023

Abstract
Worldwide, pregnancy at age 35 or older, termed ‘advanced maternal age (AMA)’, is increasing exponentially. As the incidence of pregnancy at AMA has increased, a growing body of evidence has suggested that AMA is also associated with increased risk for adverse maternal and fetal outcomes outside of genetic anomalies. Importantly, despite the mounting evidence and the increased global risk of adverse perinatal outcomes observed, few studies have examined the potential mechanisms underlying this elevated risk in pregnant people ≥35 years of age. Wooldridge and colleagues begin to address this gap in the literature. In their recent report, they examine vessel stiffness in omental resistance vessels obtained from pregnant individuals ≥35 years of age compared with pregnant individuals &lt;35 years of age. Omental arteries were isolated and assessed via pressure myography (mechanical properties) and histological analysis for collagen and elastin content. Overall, the findings from this investigation report that maternal resistance arteries collected from women of AMA were less compliant and had less elastin than arteries obtained from women &lt;35 years of age, suggesting that maternal resistance vessel stiffening in AMA may contribute to increased risk of adverse pregnancy outcomes. The authors should be commended for completing these studies in human resistance vessels, which now open new avenues for investigation and provoke a cascade of questions related to maternal cardiovascular adaptations to pregnancy in women ≥35 years of age.
Scene context‐aware graph convolutional network for skeleton‐based action recognition
Authors: Zhang Wenxian 
Published: November 2023

AbstractSkeleton‐based action recognition methods commonly employ graph neural networks to learn different aspects of skeleton topology information However, these methods often struggle to capture contextual information beyond the skeleton topology. To address this issue, a Scene Context‐aware Graph Convolutional Network (SCA‐GCN) that leverages potential contextual information in the scene is proposed. Specifically, SCA‐GCN learns the co‐occurrence probabilities of actions in specific scenarios from a common knowledge base and fuses these probabilities into the original skeleton topology decoder, producing more robust results. To demonstrate the effectiveness of SCA‐GCN, extensive experiments on four widely used datasets, that is, SBU, N‐UCLA, NTU RGB + D, and NTU RGB + D 120 are conducted. The experimental results show that SCA‐GCN surpasses existing methods, and its core idea can be extended to other methods with only some concatenation operations that consume less computational complexity.
Dynamic multi‐agent dc‐bus reconfiguration in modular motor drives with a stacked polyphase bridge converter
Authors: Verkroost Lynn , Vande Ghinste Alexander , da Rocha Lorrana Faria , De Kooning Jeroen D. M. , De Belie Frederik , Sergeant Peter , Olsen Pål Keim , Vansompel Hendrik 
Published: November 2023

AbstractA stacked polyphase bridge converter consists of multiple standard, three‐phase two‐level voltage source inverters connected in series to the same dc voltage source. The authors present a decentralised and dynamic dc‐bus reconfiguration strategy for this type of converter. The innovation of the proposed strategy lies in its ability to isolate or reactivate one of the inverters in the series connection online, even in motoring mode, enabling increased fault tolerance and an extended speed range. Both the required hardware alterations and the multi‐agent control strategy are addressed. Its major benefits compared to the state‐of‐the‐art are that only two additional active, unidirectional semiconductor switches are required per inverter, and that the control is based on local computations, local measurements and neighbour‐to‐neighbour communication only. Hence, the scalability and reliability of the hardware are extended towards the control. Simulations and experimental results on a 4 kW modular axial‐flux PMSM prove the feasibility of the concept, and validate that the dc‐bus can be reconfigured in 100 ms, without torque interruption.
Hosting capacity of distribution networks for controlled and uncontrolled residential EV charging with static and dynamic thermal ratings of network components
Authors: Zakaria As’ad , Duan Chengyan , Djokic Sasa Z. 
Published: November 2023

AbstractThe ongoing electrification of road transportation sector, which is expected to continue to strongly increase over the next years, will result in the connection of a significant number of electric vehicle (EV) chargers in LV and MV distribution networks, particularly in residential applications with on‐board (“slow”) EV chargers. In order to evaluate loading limits of existing distribution networks for the maximum number of EV chargers that can be safely connected (commonly denoted as a network EV “hosting capacity”, HC), this paper introduces a general approach to determine one commonly used network design parameter (after‐diversity maximum demand, ADMD) and one new parameter (maximum daily energy demand, MDED), which are both obtained from the load profiles of maximum per‐hour demands for uncontrolled residential EV charging. The presented approach uses actual EV charging data from the UK as the inputs in Monte Carlo simulations to generate daily EV charging profiles for arbitrary numbers of EVs, enabling to identify related ADMD, MDED and per‐hour maximum demand values, as well as their seasonal variations. The assessed ADMD, MDED and hourly maximum EV charging demands for uncontrolled EV charging are then combined with available UK residential daily load profiles before the EVs are connected (“pre‐EV demands”), where their combined coincidental and noncoincidental maximum demands are evaluated against the static thermal rating (STR) and dynamic thermal rating (DTR) loading limits of network components (transformers and overhead lines), taking into account relevant weather/ambient conditions. This is denoted as a network HC for uncontrolled EV charging. Finally, evaluating the resulting per‐hour maximum demand values against the STR and DTR loading limits and MDED values allows to select one particular scheduling method for controlled EV charging, which gives the absolute maximum number of EVs that can be safely connected in the considered network, that is, maximum network HC for fully controlled EV charging. The presented approach is illustrated on the example of the IEEE 33‐bus test network (modelled using typical UK network components), for the pre‐EV residential demands taken from the recordings at a UK MV substation, and for ambient data taken from a UK Met Office weather station. Obtained results allow to evaluate the range of network EV HC values for uncontrolled and controlled EV charging, that is, lower and upper HC limits, which can be correlated with the commonly used allocations of the firm and non‐firm network HC, respectively.
Synthetic populations of protoplanetary disks: Impact of magnetic fields and radiative transfer
Authors: Lebreuilly U. , Hennebelle P. , Colman T. , Maury A. , Tung N. D. , Testi L. , Klessen R. , Molinari S. , Commerçon B. , González M. , Pacetti E. , Somigliana A. , Rosotti G. 
Published: November 2023

Context. Protostellar disks are the product of angular momentum conservation during protostellar collapse. Understanding their formation is crucial because they are the birthplace of planets and their formation is also tightly related to star formation. Unfortunately, the initial properties of Class 0 disks and their evolution are still poorly constrained both theoretically and observationally.
Aims. We aim to better understand the mechanisms that set the statistics of disk properties as well as to study their formation in massive protostellar clumps. We also want to provide the community with synthetic disk populations to better interpret young disk observations.
Methods. We used the ramses code to model star and disk formation in massive protostellar clumps with magnetohydrodynamics, including the effect of ambipolar diffusion and radiative transfer as well as stellar radiative feedback. Those simulations, resolved up to the astronomical unit scale, have allowed us to investigate the formation of disk populations.
Results. Magnetic fields play a crucial role in disk formation. A weaker initial field leads to larger and massive disks and weakens the stellar radiative feedback by increasing fragmentation. We find that ambipolar diffusion impacts disk and star formation and leads to very different disk magnetic properties. The stellar radiative feedback also have a strong influence, increasing the temperature and reducing fragmentation. Comparing our disk populations with observations reveals that our models with a mass-to-flux ratio of 10 seems to better reproduce observed disk sizes. This also sheds light on a tension between models and observations for the disk masses.
Conclusions. The clump properties and physical modeling significantly impact disk populations. It is critical to for the tension, with respect to disk mass estimates, between observations and models to be solved with synthetic observations. This is particularly important in the context of understanding planet formation.