bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comprehensive empirical investigation of Galactic fast-rotating O-type stars
Authors: Britavskiy N. , Holgado G. , Simón-Díaz S. , Maíz Apellániz J. , Pantaleoni González M. , Nazé Y. , Burssens S. , Eldridge J. J. 
Published: August 2024

AbstractRotation is one of the important parameters affecting the evolution and final fate of massive stars but the origin of fast rotators remains unclear (imprint of the star formation process, result of binary interactions). In this work, we aim at investigating the binary status, photometric variability, and runaway status of a statistically meaningful sample of Galactic fast-rotating O stars. We perform a comprehensive multi-epoch analysis of new high-quality spectroscopic observations gathered by the IACOB and OWN surveys. Notably, we find that the total percentage of spectroscopic binaries in the investigated sample range between 25 and 40%, in agreement with previous finding for the case of O-type stars with lower projected rotational velocities. On the contrary, the fraction of runaway stars among fast rotators (∼35–50%) is significantly higher than in the case of slow rotators (∼20–30%). By combining all these observational results we will evaluate each scenario about the origin of fast rotators.
Astro+: Design, construction, and scientific exploitation of a large-scale massive star spectroscopic database
Authors: Rübke Klaus , Marco Amparo , Negueruela Ignacio , Herrero Artemio , Simon-Diaz Sergio , Tabernero Hugo , Patrick Lee 
Published: August 2024

AbstractMassive stars are the objects that condition the evolution of the interstellar medium by the amount of energy released during their lives and especially by their death as a supernova explosion. All the data provided by the previous and ongoing missions of ground and space telescopes have saturated us with the amount of information, which is no longer easy to process daily by human routines. To this end, we present the development of a massive star spectroscopic interactive database designed for scientific research.
Stellar Structure and Evolution of Massive Rotating Single Stars
Authors: Hirschi R. , Kaiser E. , Eggenberger P. , Ekström S. , Georgy C. , Maeder A. , Meynet G. 
Published: August 2024

AbstractRotation plays an important role in the structure and evolution of massive stars. It leads to deviation from spherical symmetry for very fast rotating stars, mixing in otherwise unmixed radiative regions and generally increased mass loss. In addition, magnetic fields interact with rotation and lead to significant transport of angular momentum. In this article, we review the various rotational and magnetic instabilities present in massive stars and their implementation in one-dimensional stellar evolution codes. We then focus on their impact on the evolution of single rotating stars. Finally, we compare rotating models to observations and discuss ways to disentangle between various uncertainties.
Massive Stars in Low-metallicity Galaxies in the CLASSY Survey
Authors: Berg Danielle A. , James Beth L. , King Teagan , McDonald Meaghan , Chen Zuyi , Chisholm John , Heckman Timothy , Martin Crystal L. , Stark Dan P. ,   The CLASSY Team
Published: August 2024

AbstractRest-frame far-ultraviolet spectra are fundamental to our understanding of star-forming galaxies, providing a unique window on massive star populations (MSs), chemical evolution, feedback processes, and reionization. JWST is ushering in a new era, pushing the FUV frontier beyond z=10. The success of such endeavors hinges on a comprehensive understanding of the MSs and gas conditions that power the observed spectra. The COS Legacy Archive Spectroscopic SurveY (CLASSY) is a powerful and promising solution providing high-quality, high-resolution FUV spectra of 45 nearby star-forming galaxies. The spectra contain a suite of features that simultaneously characterize the MSs that populate metal-poor galaxies, physical properties of large-scale outflows, and chemical abundance patterns. The CLASSY sample is consistent with the z 0 mass-metallicity relationship and spans 1.5 dex in metallicity. These unique properties make CLASSY the benchmark training set for studies of MSs in star-forming galaxies both across cosmic time and connecting metal-poor to metal-rich populations.
CMD for atmospheres of massive stars created by using CMFGEN synthetic spectra
Authors: Arrieta Anabel , Payen-Sandoval Agustín , Arias Lorena , Zsargo Janos , Fierro-Santillán Celia , Klapp Jaime 
Published: August 2024

AbstractWe present Color Magnitude Diagrams (CMDs) created by using our database of 43,340 synthetic CMFGEN spectra. For each calculated spectra we measure the absolute flux by Johnson and Gaia photometry filters and build synthetic CMDs.
Integration of DDPM and ILUES for Simultaneous Identification of Contaminant Source Parameters and Non‐Gaussian Channelized Hydraulic Conductivity Field
Authors: Zhang Xun , Jiang Simin , Zheng Na , Xia Xuemin , Li Zhi , Zhang Ruicheng , Zhang Jiangjiang , Wang Xinshu 
Published: August 2024

AbstractIdentifying highly channelized hydraulic conductivity fields and contaminant source parameters remains a challenging task, primarily due to the non‐Gaussian nature and high dimensionality of the parameter space, as well as the computational burden caused by repeatedly running forward numerical models. This study proposes a novel deep learning parameterization method called AEdiffusion, which combines Diffusion Denoising Probabilistic Model (DDPM) with Variational Autoencoder (VAE) for dimensionality reduction. The method employs a generator‐refiner strategy to generate high‐dimensional aquifer properties from low‐dimensional latent representations. The inversion modeling was performed on a synthetic non‐Gaussian hydraulic conductivity field with line‐source contamination using the Iterative Local Updating Ensemble Smoother (ILUES) algorithm. The results demonstrate that the AEdiffusion‐ILUES framework can accurately identify model parameters. To reduce the computational burden, an AR‐Net‐WL (ARNW) surrogate model was introduced, resulting in an efficient inversion framework (AEdiffusion‐ILUES‐ARNW) with similar prediction accuracy and predictive uncertainty estimation as the AEdiffusion‐ILUES but at a lower computational cost.
Evaluation of Modeled Diurnal Warming Estimates for Application to Producing Sea Surface Temperature Analyses
Authors: Wick Gary A. , Castro Sandra L. , Harris Andrew , Mittaz Jonathan 
Published: August 2024

AbstractAccurate knowledge of the amount of diurnal warming present in sea surface temperature (SST) observations at different times and effective depths is important for multiple applications including the production of blended SST analyses. This work explores the ability of a modified Kantha‐Clayson‐type one‐dimensional mixed layer ocean model with wave effects to accurately simulate the observed diurnal warming amplitude over a global grid when forced with coarse resolution numerical weather prediction (NWP) outputs. The sensitivity of the modeled diurnal amplitudes to multiple adjustable parameters and model configurations is evaluated to determine whether a preferred configuration can be identified that yields reliable predictions. The accuracy of the predictions is determined through comparison against estimates from operational SST retrievals from geostationary satellites. The results show that a single configuration can yield predictions that reproduce the observed range of diurnal warming amplitudes across a range of seasons and locations and an accurate occurrence frequency of the largest amplitude events. Simulated amplitudes fall along the one‐to‐one line with observations but with significant scatter due to factors including positioning of the NWP fluxes. The identified configuration is also shown to favorably reproduce diurnal warming observations from multiple research cruises. Overall uncertainty of the simulated diurnal warming amplitude across the different tests ranges between 0.4 K for all observations to ∼1 K for the largest warming events. While the focus is not on model comparisons, the results show improved performance relative to other models. Use of the model appears warranted but the associated uncertainty must be considered.
Nanomedicine-induced programmed cell death in cancer therapy: mechanisms and perspectives
Authors: Luobin Lin , Wanxin He , Yingxin Guo , Qinzhou Zheng , Zefeng Liang , Danyang Wu , Huaqin Li 
Published: August 2024

AbstractThe balance of programmed cell death (PCD) mechanisms, including apoptosis, autophagy, necroptosis and others, is pivotal in cancer progression and treatment. Dysregulation of these pathways results in uncontrolled cell growth and resistance to conventional therapies. Nanomedicine offers a promising solution in oncology through targeted drug delivery enabling precise targeting of cancer cells while preserving healthy tissues. This approach reduces the side effects of traditional chemotherapy and enhances treatment efficacy by engaging PCD pathways. We details each PCD pathway, their mechanisms, and innovative nanomedicine strategies to activate these pathways, thereby enhancing therapeutic specificity and minimizing harm to healthy tissues. The precision of nanotechnology in targeting PCD pathways promises significant improvements in cancer treatment outcomes. This synergy between nanotechnology and targeted PCD activation could lead to more effective and less toxic cancer therapies, heralding a new era in cancer treatment.
GRK2-mediated AKT activation controls cell cycle progression and G2 checkpoint in a p53-dependent manner
Authors: Rivas Verónica , González-Muñoz Teresa , Albitre Ángela , Lafarga Vanesa , Delgado-Arévalo Cristina , Mayor Federico , Penela Petronila 
Published: August 2024

AbstractCell cycle checkpoints, activated by stressful events, halt the cell cycle progression, and prevent the transmission of damaged DNA. These checkpoints prompt cell repair but also trigger cell death if damage persists. Decision-making between these responses is multifactorial and context-dependent, with the tumor suppressor p53 playing a central role. In many tumor cells, p53 alterations lead to G1/S checkpoint loss and the weakening of the G2 checkpoint, rendering cell viability dependent on the strength of the latter through mechanisms not fully characterized. Cells with a strong pro-survival drive can evade cell death despite substantial DNA lesions. Deciphering the integration of survival pathways with p53-dependent and -independent mechanisms governing the G2/M transition is crucial for understanding G2 arrest functionality and predicting tumor cell response to chemotherapy. The serine/threonine kinase GRK2 emerges as a signaling node in cell cycle modulation. In cycling cells, but not in G2 checkpoint-arrested cells, GRK2 protein levels decline during G2/M transition through a process triggered by CDK2-dependent phosphorylation of GRK2 at the S670 residue and Mdm2 ubiquitination. We report now that this downmodulation in G2 prevents the unscheduled activation of the PI3K/AKT pathway, allowing cells to progress into mitosis. Conversely, higher GRK2 levels lead to tyrosine phosphorylation by the kinase c-Abl, promoting the direct association of GRK2 with the p85 regulatory subunit of PI3K and AKT activation in a GRK2 catalytic-independent manner. Hyperactivation of AKT is conditioned by p53’s scaffolding function, triggering FOXO3a phosphorylation, impaired Cyclin B1 accumulation, and CDK1 activation, causing a G2/M transition delay. Upon G2 checkpoint activation, GRK2 potentiates early arrest independently of p53 through AKT activation. However, its ability to overcome the G2 checkpoint in viable conditions depends on p53. Our results suggest that integrating the GRK2/PI3K/AKT axis with non-canonical functions of p53 might confer a survival advantage to tumor cells.
Perspective: Clinical care of pedophilic individuals in Zurich, Switzerland
Authors: de Tribolet-Hardy Fanny , Veitz Simon , Dittli Laura , Habermeyer Elmar 
Published: August 2024

AbstractIndividuals with pedophilia are considered to have an elevated risk for child sexual abuse (CSA). Nevertheless, it is assumed that pedophilic sexual impulses can be controlled from acting out. To prevent CSA an outpatient treatment facility for people with pedophilia was founded in Zurich, Switzerland in 2021. The program focuses on the prevention of CSA and improvement of quality of life, incorporating empirically validated treatment principles, such as the Risk-Need-Responsivity (RNR) model and the Good Lives Model (GLM). Within the initial 24-month 142 individuals sought help, 46 individuals (mean age 36.0 ± 12.4 years) completed the assessment phase, two-thirds suffered from psychiatric comorbidities, and 67.4% reported sexual delinquency. The high drop-out rate was predominantly due to ongoing criminal proceedings, or other mental health conditions. Overall patients at this facility generally sought treatment voluntarily, leading to good treatment adherence, with severe self-harm being more prevalent than acute danger to others. A treatment approach focused solely on pedophilia is considered insufficient; psychiatric and psychosocial factors must also be addressed.
Optimising CNT-FET biosensor design through modelling of biomolecular electrostatic gating and its application to β-lactamase detection
Authors: Gwyther Rebecca E. A. , Côté Sébastien , Lee Chang-Seuk , Miao Haosen , Ramakrishnan Krithika , Palma Matteo , Dafydd Jones D. 
Published: August 2024

AbstractCarbon nanotube field effect transistors (CNT-FET) hold great promise as next generation miniaturised biosensors. One bottleneck is modelling how proteins, with their distinctive electrostatic surfaces, interact with the CNT-FET to modulate conductance. Using advanced sampling molecular dynamics combined with non-canonical amino acid chemistry, we model protein electrostatic potential imparted on single walled CNTs (SWCNTs). We focus on using β-lactamase binding protein (BLIP2) as the receptor as it binds the antibiotic degrading enzymes, β-lactamases (BLs). BLIP2 is attached via the single selected residue to SWCNTs using genetically encoded phenyl azide photochemistry. Our devices detect two different BLs, TEM-1 and KPC-2, with each BL generating distinct conductance profiles due to their differing surface electrostatic profiles. Changes in conductance match the model electrostatic profile sampled by the SWCNTs on BL binding. Thus, our modelling approach combined with residue-specific receptor attachment could provide a general approach for systematic CNT-FET biosensor construction.
Spatially controllable and mechanically switchable isomorphous organoferroeleastic crystal optical waveguides and networks
Authors: Ranjan Subham , Kumar Avulu Vinod , Chandrasekar Rajadurai , Takamizawa Satoshi 
Published: August 2024

AbstractThe precise, reversible, and diffusionless shape-switching ability of organic ferroelastic crystals, while maintaining their structural integrity, positions them as promising materials for next-generation hybrid photonic devices. Herein, we present versatile bi-directional ferroelasticity and optical waveguide properties of three isomorphous, halogen-based, Schiff base organic crystals. These crystals exhibit sharp bending at multiple interfaces driven by molecular movement around the CH = N bond and subsequent 180° rotational twinning, offering controlled light path manipulation. The ferroelastic nature of these crystals allowed the construction of robust hybrid photonic structures, including Z-shaped configurations, closed-loop networks, and staircase-like hybrid optical waveguides. This study highlights the potential of shape-switchable organoferroelastic crystals as waveguides for applications in programmable photonic devices.
Tough double-bouligand architected concrete enabled by robotic additive manufacturing
Authors: Prihar Arjun , Gupta Shashank , Esmaeeli Hadi S. , Moini Reza 
Published: August 2024

AbstractNature has developed numerous design motifs by arranging modest materials into complex architectures. The damage-tolerant, double-bouligand architecture found in the coelacanth fish scale is comprised of collagen fibrils helically arranged in a bilayer manner. Here, we exploit the toughening mechanisms of double-bouligand designs by engineering architected concrete using a large-scale two-component robotic additive manufacturing process. The process enables intricate fabrication of the architected concrete components at large-scale. The double-bouligand designs are benchmarked against bouligand and conventional rectilinear counterparts and monolithic casts. In contrast to cast concrete, double-bouligand design demonstrates a non-brittle response and a rising R-curve, due to a hypothesized bilayer crack shielding mechanism. In addition, interlocking behind and crack deflection ahead of the crack tip in bilayer double-bouligand architected concrete elicits a 63% increase in fracture toughness compared to cast counterparts.
Adipocyte deletion of the oxygen-sensor PHD2 sustains elevated energy expenditure at thermoneutrality
Authors: Wang Rongling , Gomez Salazar Mario , Pruñonosa Cervera Iris , Coutts Amanda , French Karen , Pinto Marlene Magalhaes , Gohlke Sabrina , García-Martín Ruben , Blüher Matthias , Schofield Christopher J. , Kourtzelis Ioannis , Stimson Roland H. , Bénézech Cécile , Christian Mark , Schulz Tim J. , Gudmundsson Elias F. , Jennings Lori L. , Gudnason Vilmundur G. , Chavakis Triantafyllos , Morton Nicholas M. , Emilsson Valur , Michailidou Zoi 
Published: August 2024

AbstractEnhancing thermogenic brown adipose tissue (BAT) function is a promising therapeutic strategy for metabolic disease. However, predominantly thermoneutral modern human living conditions deactivate BAT. We demonstrate that selective adipocyte deficiency of the oxygen-sensor HIF-prolyl hydroxylase (PHD2) gene overcomes BAT dormancy at thermoneutrality. Adipocyte-PHD2-deficient mice maintain higher energy expenditure having greater BAT thermogenic capacity. In human and murine adipocytes, a PHD inhibitor increases Ucp1 levels. In murine brown adipocytes, antagonising the major PHD2 target, hypoxia-inducible factor-(HIF)−2a abolishes Ucp1 that cannot be rescued by PHD inhibition. Mechanistically, PHD2 deficiency leads to HIF2 stabilisation and binding of HIF2 to the Ucp1 promoter, thus enhancing its expression in brown adipocytes. Serum proteomics analysis of 5457 participants in the deeply phenotyped Age, Gene and Environment Study reveal that serum PHD2 associates with increased risk of metabolic disease. Here we show that adipose-PHD2-inhibition is a therapeutic strategy for metabolic disease and identify serum PHD2 as a disease biomarker.
Variations of organic functional chemistry in carbonaceous matter from the asteroid 162173 Ryugu
Authors: De Gregorio Bradley , Cody George D. , Stroud Rhonda M. , David Kilcoyne A. L. , Sandford Scott , Le Guillou Corentin , Nittler Larry R. , Barosch Jens , Yabuta Hikaru , Martins Zita , Kebukawa Yoko , Okumura Taiga , Hashiguchi Minako , Yamashita Shohei , Takeichi Yasuo , Takahashi Yoshio , Wakabayashi Daisuke , Engrand Cécile , Bejach Laure , Bonal Lydie , Quirico Eric , Remusat Laurent , Duprat Jean , Verdier-Paoletti Maximilien , Mostefaoui Smail , Komatsu Mutsumi , Mathurin Jérémie , Dazzi Alexandre , Deniset-Besseau Ariane , Dartois Emmanuel , Tamenori Yusuke , Suga Hiroki , Montagnac Gilles , Kamide Kanami , Shigenaka Miho , Matsumoto Megumi , Enokido Yuma , Yoshikawa Makoto , Saiki Takanao , Tanaka Satoshi , Terui Fuyuto , Nakazawa Satoru , Usui Tomohiro , Abe Masanao , Okada Tatsuaki , Yada Toru , Nishimura Masahiro , Nakato Aiko , Miyazaki Akiko , Yogata Kasumi , Yurimoto Hisayoshi , Nakamura Tomoki , Noguchi Takaaki , Okazaki Ryuji , Naraoka Hiroshi , Sakamoto Kanako , Tachibana Shogo , Watanabe Sei-ichiro , Tsuda Yuichi 
Published: August 2024

AbstractPrimordial carbon delivered to the early earth by asteroids and meteorites provided a diverse source of extraterrestrial organics from pre-existing simple organic compounds, complex solar-irradiated macromolecules, and macromolecules from extended hydrothermal processing. Surface regolith collected by the Hayabusa2 spacecraft from the carbon-rich asteroid 162173 Ryugu present a unique opportunity to untangle the sources and processing history of carbonaceous matter. Here we show carbonaceous grains in Ryugu can be classified into three main populations defined by spectral shape: Highly aromatic (HA), Alkyl-Aromatic (AA), and IOM-like (IL). These carbon populations may be related to primordial chemistry, since C and N isotopic compositions vary between the three groups. Diffuse carbon is occasionally dominated by molecular carbonate preferentially associated with coarse-grained phyllosilicate minerals. Compared to related carbonaceous meteorites, the greater diversity of organic functional chemistry in Ryugu indicate the pristine condition of these asteroid samples.
Leveraging artificial intelligence to identify the psychological factors associated with conspiracy theory beliefs online
Authors: Kunst Jonas R. , Gundersen Aleksander B. , Krysińska Izabela , Piasecki Jan , Wójtowicz Tomi , Rygula Rafal , van der Linden Sander , Morzy Mikolaj 
Published: August 2024

AbstractGiven the profound societal impact of conspiracy theories, probing the psychological factors associated with their spread is paramount. Most research lacks large-scale behavioral outcomes, leaving factors related to actual online support for conspiracy theories uncertain. We bridge this gap by combining the psychological self-reports of 2506 Twitter (currently X) users with machine-learning classification of whether the textual data from their 7.7 million social media engagements throughout the pandemic supported six common COVID-19 conspiracy theories. We assess demographic factors, political alignment, factors derived from theory of reasoned action, and individual psychological differences. Here, we show that being older, self-identifying as very left or right on the political spectrum, and believing in false information constitute the most consistent risk factors; denialist tendencies, confidence in one’s ability to spot misinformation, and political conservativism are positively associated with support for one conspiracy theory. Combining artificial intelligence analyses of big behavioral data with self-report surveys can effectively identify and validate risk factors for phenomena evident in large-scale online behaviors.