bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tracing Recycled Crustal Materials in the Subcontinental Lithospheric Mantle Using Thallium Isotopes
Authors: Mei Qing‐Feng , Chen Xinming , Yang Jin‐Hui , Zhu Yu‐Sheng , Owens Jeremy D. 
Published: August 2022

AbstractHere we report the first set of thallium (Tl) isotope data in alkaline rocks from the North China Craton to constrain the nature of recycled materials in the metasomatized subcontinental lithospheric mantle. Samples from the Hekanzi and Saima alkaline complexes display Tl isotope compositions (ε205Tl) identical to the present‐day upper mantle and continental crust, suggesting that neither the recycled low‐temperature altered oceanic crust nor the pelagic sediments were involved in their sources. The volcanic rocks from the Liaodong‐Jinan region, whose source was previously proposed to contain recycled low‐temperature altered oceanic crust, also display modern mantle‐like Tl isotope composition, suggesting a significant Tl‐loss in the recycled oceanic crust during the subduction due to the dehydration process. Our Tl isotope data provide complementary constraints to the Sr‐Nd‐Hf‐O isotopes on the nature of metasomatic agent in the subcontinental lithospheric mantle.
Complex Patterns of Past and Ongoing Crustal Deformations in Southern California Revealed by Seismic Azimuthal Anisotropy
Authors: Wu Shucheng , Jiang Chengxin , Schulte‐Pelkum Vera , Tong Ping 
Published: August 2022

AbstractWe present a high‐resolution P‐wave azimuthally anisotropic velocity model for the upper and middle crust beneath southern California by a novel adjoint‐state traveltime tomography technique. Our model reveals significant anisotropy variations between tectonic blocks that clearly reflect both past and current plate boundary deformation. In the shallow crust, seismic anisotropy is mostly controlled by the preferred alignment of microcracks related to the present N‐S compressive stress; while at deeper depths (>∼6 km), seismic anisotropy mainly records paleofabrics formed during the long‐lived Farallon subduction and later extension that have not been fully reset by the present transform motion. Interestingly, our model demonstrates distinct fast axes beneath the western Transverse Ranges from its neighboring blocks, probably reflecting the large‐scale vertical axis clockwise rotation of the block. In addition, we identify layered structures with distinct anisotropy features beneath the Salton Trough, which could be a result of the current transtension.
Quantifying Large‐Scale Surface Change Using SAR Amplitude Images: Crater Morphology Changes During the 2019–2020 Shishaldin Volcano Eruption
Authors: Angarita M. , Grapenthin R. , Plank S. , Meyer F. J. , Dietterich H. 
Published: August 2022

AbstractMorphological processes often induce meter‐scale elevation changes. When a volcano erupts, tracking such processes provides insights into the style and evolution of eruptive activity and related hazards. Compared to optical remote‐sensing products, synthetic aperture radar (SAR) observes surface change during inclement weather and at night. Differential SAR interferometry estimates phase change between SAR acquisitions and is commonly applied to quantify deformation. However, large deformation or other coherence loss can limit its use. We develop a new approach applicable when repeated digital elevation models (DEMs) cannot be otherwise retrieved. Assuming an isotropic radar cross‐section, we estimate meter‐scale vertical morphological change directly from SAR amplitude images via an optimization method that utilizes a high‐quality DEM. We verify our implementation through simulation of a collapse feature that we modulate onto topography. We simulate radar effects and recover the simulated collapse. To validate our method, we estimate elevation changes from TerraSAR‐X stripmap images for the 2011–2012 eruption of Mount Cleveland. Our results reproduce those from two previous studies; one that used the same dataset, and another based on thermal satellite data. By applying this method to the 2019–2020 eruption of Shishaldin Volcano, Alaska, we generate elevation change time series from dozens of co‐registered TerraSAR‐X high‐resolution spotlight images. Our results quantify previously unresolved cone growth in November 2019, collapses associated with explosions in December–January, and further changes in crater elevations into spring 2020. This method can be used to track meter‐scale morphology changes for ongoing eruptions with low latency as SAR imagery becomes available.
Modeling Radiation Belt Electrons With Information Theory Informed Neural Networks
Authors: Wing Simon , Turner Drew L. , Ukhorskiy Aleksandr Y. , Johnson Jay R. , Sotirelis Thomas , Nikoukar Romina , Romeo Giuseppe 
Published: August 2022

AbstractAn empirical model of radiation belt relativistic electrons (μ = 560–875 MeV G−1 and I = 0.088–0.14 RE G0.5) with average energy ∼1.3 MeV is developed. The model inputs solar wind parameters (velocity, density, interplanetary magnetic field (IMF) |B|, Bz, and By), magnetospheric state parameters (SYM‐H and AL), and L*. The model outputs the radiation belt electron phase space density (PSD). The model is operational from L* = 3 to 6.5. The model is constructed with neural networks assisted by information theory. Information theory is used to select the most effective and relevant solar wind and magnetospheric input parameters plus their lag times based on their information transfer to the PSD. Based on the test set, the model prediction efficiency (PE) increases with increasing L*, ranging from −0.043 at L* = 3 to 0.76 at L* = 6.5. The model PE is near 0 at L* = 3–4 because at this L* range, the solar wind and magnetospheric parameters transfer little information to the PSD. Using solar wind observations at L1 and magnetospheric index (AL and SYM‐H) models solely driven by solar wind, the radiation belt model can be used to forecast PSD 30–60 min ahead. This baseline model can potentially complement a class of empirical models that input data from low earth orbit (LEO).
Decoherence of nitrogen-vacancy spin ensembles in a nitrogen electron-nuclear spin bath in diamond
Authors: Park Huijin , Lee Junghyun , Han Sangwook , Oh Sangwon , Seo Hosung 
Published: August 2022

AbstractNitrogen-vacancy (NV) centers in diamond have been developed into essential hardware units for a wide range of solid-state-based quantum technology applications. While such applications require the long spin coherence times of the NV centers, they are often limited due to decoherence. In this study, we theoretically investigate the decoherence of NV-spin ensembles induced by nitrogen impurities (P1 centers), which are one of the most dominant and inevitable magnetic field noise sources in diamond. We combined cluster correlation expansion and density functional theory to compute the Hahn-echo spin-coherence time of the NV centers for a broad range of P1 concentrations. Results indicate a clear linear dependence of T2 on P1 concentrations on a log scale with a slope of −1.06, which is in excellent agreement with previous experimental results. The interplay between the Jahn–Teller effect and the hyperfine interaction in the P1 center plays a critical role in determining the bath dynamics and the resulting NV decoherence. Our results provide a theoretical upper bound for the NV-spin T2 over a wide range of P1 densities, serving as a key reference for materials optimization and spin bath characterization to develop highly coherent NV-based devices for quantum information technology.
Spatially resolved clonal copy number alterations in benign and malignant tissue
Authors: Erickson Andrew , He Mengxiao , Berglund Emelie , Marklund Maja , Mirzazadeh Reza , Schultz Niklas , Kvastad Linda , Andersson Alma , Bergenstråhle Ludvig , Bergenstråhle Joseph , Larsson Ludvig , Alonso Galicia Leire , Shamikh Alia , Basmaci Elisa , Díaz De Ståhl Teresita , Rajakumar Timothy , Doultsinos Dimitrios , Thrane Kim , Ji Andrew L. , Khavari Paul A. , Tarish Firaz , Tanoglidi Anna , Maaskola Jonas , Colling Richard , Mirtti Tuomas , Hamdy Freddie C. , Woodcock Dan J. , Helleday Thomas , Mills Ian G. , Lamb Alastair D. , Lundeberg Joakim 
Published: August 2022

AbstractDefining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.
Neural network analysis of quasistationary magnetic fields in microcoils driven by short laser pulses
Authors: Kochetkov Iu. V. , Bukharskii N. D. , Ehret M. , Abe Y. , Law K. F. F. , Ospina-Bohorquez V. , Santos J. J. , Fujioka S. , Schaumann G. , Zielbauer B. , Kuznetsov A. , Korneev Ph. 
Published: August 2022

AbstractOptical generation of kilo-tesla scale magnetic fields enables prospective technologies and fundamental studies with unprecedentedly high magnetic field energy density. A question is the optimal configuration of proposed setups, where plenty of physical phenomena accompany the generation and complicate both theoretical studies and experimental realizations. Short laser drivers seem more suitable in many applications, though the process is tangled by an intrinsic transient nature. In this work, an artificial neural network is engaged for unravelling main features of the magnetic field excited with a picosecond laser pulse. The trained neural network acquires an ability to read the magnetic field values from experimental data, extremely facilitating interpretation of the experimental results. The conclusion is that the short sub-picosecond laser pulse may generate a quasi-stationary magnetic field structure living on a hundred picosecond time scale, when the induced current forms a closed circuit.
Microstructural and nanoindentation study of TaN incorporated ZrB2 and ZrB2–SiC ceramics
Authors: Delbari Seyed Ali , Namini Abbas Sabahi , Lee Seonyong , Jung Sunghoon , Wang Jinghan , Lee Sea-Hoon , Cha Joo Hwan , Cho Jin Hyuk , Jang Ho Won , Kim Soo Young , Shokouhimehr Mohammadreza 
Published: August 2022

AbstractThis study assessed the sinterability and microstructure of ZrB2-SiC-TaN and ZrB2-TaN ceramics. Spark plasma sintering at 2000 °C and 30 MPa for 5 min produced both ceramics. The relative density of ZrB2 ceramic containing TaN was 95.3%; the addition of SiC increased this value to 98.1%. SiC’s contribution to the elimination of ZrB2 surface oxides was the primary factor in the advancement of densification. The in situ formation of hexagonal boron nitride at the interface of TaN and ZrB2 was confirmed by high-resolution transmission electron microscopy, field emission-electron probe microanalyzer, X-ray diffractometry, and field emission scanning electron microscopy. Moreover, the in situ graphite might be produced as a byproduct of the SiC-SiO2 process, hence boosting the reduction of oxide compounds in the ternary system. The SiC compound had the highest hardness (29 ± 3 GPa), while the ZrB2/TaN interface exhibited the greatest values of elastic modulus (473 ± 26 GPa) and stiffness (0.76 ± 0.13 mN/nm).
Deviation from the planned axis of three toric intraocular lenses
Authors: Sheen-Ophir Shira , Reitblat Olga , Levy Adi , Assia Ehud I. , Kleinmann Guy 
Published: August 2022

AbstractIn this study, we retrospectively evaluated the deviation from the planned axis of 3 Toric intraocular lenses (TIOL). Included in the study 190 eyes, operated by two surgeons using two different manual marking techniques. The patients were implanted with either AcrySof IQ Toric SN6AT (Alcon) (n = 90), POD FT (PhysIOL) (n = 50), or TECNIS Symfony Toric (J&J) (n = 50). At least 1 month postoperatively, the IOL was photographed, and the axis was measured using a designed software. The difference between the planned and actual axis was defined as axis deviation. The effect of IOL type, astigmatism direction, and marking techniques on the average degree and direction of the IOL deviation were evaluated and compared. There was no significant difference in the average deviation between the IOLs (TECNIS Symfony: 4.03° ± 4.34, POD FT: 3.52° ± 3.38, and SN6AT: 4.24° ± 4.10), and its direction (55.8%, 39.0%, and 56.6% clockwise (CW) deviation, respectively). With the rule, astigmatism had significantly more CW deviation compared with against the rule and oblique astigmatism (64.3%, 43.8%, and 41.7%, respectively, P = 0.027), but the average deviation was similar. The marking techniques did not influence the degree or direction of the deviation.
Improvement in the neutron beam collimation for application in boron neutron capture therapy of the head and neck region
Authors: Hu Naonori , Tanaka Hiroki , Kakino Ryo , Yoshikawa Syuushi , Miyao Mamoru , Akita Kazuhiko , Aihara Teruhito , Nihei Keiji , Ono Koji 
Published: August 2022

AbstractIn June 2020, the Japanese government approved boron neutron capture therapy for the treatment of head and neck cancer. The treatment is usually performed in a single fraction, with the neutron irradiation time being approximately 30–60 min. As neutrons scatter in air and loses its intensity, it is preferable to bring the patient as close to the beam port as possible to shorten the irradiation time. However, this can be a challenge, especially for patients with head and neck cancer, as the shoulders are an obstacle to a clean positioning. In this study, a novel neutron collimation system for an accelerator based neutron source was designed to allow for a more comfortable treatment, without compromising the irradiation time. Experimental measurements confirmed the simulation results and showed the new collimator can reduce the irradiation time by approximately 60% (under the same condition where the distance between the source and the patient surface was kept the same). The dose delivered to the surrounding healthy tissue was reduced with the new collimator, showing a 25% decrease in the D50 of the mucosal membrane. Overall, the use of the newly designed collimator will allow for a more comfortable treatment of the head and neck region, reduce the treatment time, and reduce the dose delivered to the surrounding healthy tissue.
Identification of novel prognostic risk signature of breast cancer based on ferroptosis-related genes
Authors: Wang Nan , Gu Yuanting , Li Lin , Chi Jiangrui , Liu Xinwei , Xiong Youyi , Jiang Shan , Zhang Wudi , Zhong Chaochao 
Published: August 2022

AbstractFerroptosis is a type of cell regulated necrosis triggered by intracellular phospholipid peroxidation, which is more immunogenic than apoptosis. Therefore, genes controlling ferroptosis may be promising candidate biomarkers for tumor therapy. In this study, we investigate the function of genes associated with ferroptosis in breast cancer (BC) and systematically evaluate the relationship between ferroptosis-related gene expression and prognosis of BC patients from the Cancer Genome Atlas database. By using the consensus clustering method, 1203 breast cancer samples were clustered into two clearly divided subgroups based on the expression of 237 ferroptosis-related genes. Then differentially expressed analysis and least absolute shrinkage and selection operator were used to identify the prognosis-related genes. Furthermore, the genetic risk signature was constructed using the expression of prognosis-related genes. Our results showed that the genetic risk signature can identify patient subgroups with distinct prognosis in either training cohort or validation, and the genetic risk signature was associated with the tumor immune microenvironment. Finally, the Cox regression analysis indicated that our risk signature was an independent prognostic factor for BC patients and this signature was verified by the polymerase chain reaction and western blot. Within this study, we identified a novel prognostic classifier based on five ferroptosis-related genes which may provide a new reference for the treatment of BRCA patients.
Interactive exploration of a global clinical network from a large breast cancer cohort
Authors: Sella Nadir , Hamy Anne-Sophie , Cabeli Vincent , Darrigues Lauren , Laé Marick , Reyal Fabien , Isambert Hervé 
Published: August 2022

AbstractDespite unprecedented amount of information now available in medical records, health data remain underexploited due to their heterogeneity and complexity. Simple charts and hypothesis-driven statistics can no longer apprehend the content of information-rich clinical data. There is, therefore, a clear need for powerful interactive visualization tools enabling medical practitioners to perceive the patterns and insights gained by state-of-the-art machine learning algorithms. Here, we report an interactive graphical interface for use as the front end of a machine learning causal inference server (MIIC), to facilitate the visualization and comprehension by clinicians of relationships between clinically relevant variables. The widespread use of such tools, facilitating the interactive exploration of datasets, is crucial both for data visualization and for the generation of research hypotheses. We demonstrate the utility of the MIIC interactive interface, by exploring the clinical network of a large cohort of breast cancer patients treated with neoadjuvant chemotherapy (NAC). This example highlights, in particular, the direct and indirect links between post-NAC clinical responses and patient survival. The MIIC interactive graphical interface has the potential to help clinicians identify actionable nodes and edges in clinical networks, thereby ultimately improving the patient care pathway.
Modeling SARS-CoV-2 and influenza infections and antiviral treatments in human lung epithelial tissue equivalents
Authors: Zarkoob Hoda , Allué-Guardia Anna , Chen Yu-Chi , Garcia-Vilanova Andreu , Jung Olive , Coon Steven , Song Min Jae , Park Jun-Gyu , Oladunni Fatai , Miller Jesse , Tung Yen-Ting , Kosik Ivan , Schultz David , Iben James , Li Tianwei , Fu Jiaqi , Porter Forbes D. , Yewdell Jonathan , Martinez-Sobrido Luis , Cherry Sara , Torrelles Jordi B. , Ferrer Marc , Lee Emily M. 
Published: August 2022

AbstractThere is a critical need for physiologically relevant, robust, and ready-to-use in vitro cellular assay platforms to rapidly model the infectivity of emerging viruses and develop new antiviral treatments. Here we describe the cellular complexity of human alveolar and tracheobronchial air liquid interface (ALI) tissue models during SARS-CoV-2 and influenza A virus (IAV) infections. Our results showed that both SARS-CoV-2 and IAV effectively infect these ALI tissues, with SARS-CoV-2 exhibiting a slower replication peaking at later time-points compared to IAV. We detected tissue-specific chemokine and cytokine storms in response to viral infection, including well-defined biomarkers in severe SARS-CoV-2 and IAV infections such as CXCL10, IL-6, and IL-10. Our single-cell RNA sequencing analysis showed similar findings to that found in vivo for SARS-CoV-2 infection, including dampened IFN response, increased chemokine induction, and inhibition of MHC Class I presentation not observed for IAV infected tissues. Finally, we demonstrate the pharmacological validity of these ALI tissue models as antiviral drug screening assay platforms, with the potential to be easily adapted to include other cell types and increase the throughput to test relevant pathogens.
PIKfyve-specific inhibitors restrict replication of multiple coronaviruses in vitro but not in a murine model of COVID-19
Authors: Logue James , Chakraborty Arup R. , Johnson Robert , Goyal Girija , Rodas Melissa , Taylor Louis J. , Baracco Lauren , McGrath Marisa E. , Haupt Robert , Furlong Brooke A. , Soong Mercy , Prabhala Pranav , Horvath Viktor , Carlson Kenneth E. , Weston Stuart , Ingber Donald E. , DePamphilis Melvin L. , Frieman Matthew B. 
Published: August 2022

AbstractThe ongoing COVID-19 pandemic has claimed more than 6 million lives and continues to test the world economy and healthcare systems. To combat this pandemic, the biological research community has shifted efforts to the development of medical countermeasures, including vaccines and therapeutics. However, to date, the only small molecules approved for the treatment of COVID-19 in the United States are the nucleoside analogue Remdesivir and the protease inhibitor Paxlovid, though multiple compounds have received Emergency Use Authorization and many more are currently being tested in human efficacy trials. One such compound, Apilimod, is being considered as a COVID-19 therapeutic in a Phase II efficacy trial. However, at the time of writing, there are no published efficacy data in human trials or animal COVID-19 models. Here we show that, while Apilimod and other PIKfyve inhibitors have potent antiviral activity in various cell lines against multiple human coronaviruses, these compounds worsen disease in a COVID-19 murine model when given prophylactically or therapeutically.
Thermodynamics of correlated electrons in a magnetic field
Authors: Ding Jixun K. , Wang Wen O. , Moritz Brian , Schattner Yoni , Huang Edwin W. , Devereaux Thomas P. 
Published: August 2022

AbstractThe Hofstadter–Hubbard model captures the physics of strongly correlated electrons in an applied magnetic field, which is relevant to many recent experiments on Moiré materials. Few large-scale, numerically exact simulations exists for this model. In this work, we simulate the Hubbard–Hofstadter model using the determinant quantum Monte Carlo (DQMC) algorithm. We report the field and Hubbard interaction strength dependence of charge compressibility, fermion sign, local moment, magnetic structure factor, and specific heat. The gross structure of magnetic Bloch bands and band gaps determined by the non-interacting Hofstadter spectrum is preserved in the presence of U. Incompressible regions of the phase diagram have improved fermion sign. At half filling and intermediate and larger couplings, a strong orbital magnetic field delocalizes electrons and reduces the effect of Hubbard U on thermodynamic properties of the system.
Discovering sparse interpretable dynamics from partial observations
Authors: Lu Peter Y. , Ariño Bernad Joan , Soljačić Marin 
Published: August 2022

AbstractIdentifying the governing equations of a nonlinear dynamical system is key to both understanding the physical features of the system and constructing an accurate model of the dynamics that generalizes well beyond the available data. Achieving this kind of interpretable system identification is even more difficult for partially observed systems. We propose a machine learning framework for discovering the governing equations of a dynamical system using only partial observations, combining an encoder for state reconstruction with a sparse symbolic model. The entire architecture is trained end-to-end by matching the higher-order symbolic time derivatives of the sparse symbolic model with finite difference estimates from the data. Our tests show that this method can successfully reconstruct the full system state and identify the equations of motion governing the underlying dynamics for a variety of ordinary differential equation (ODE) and partial differential equation (PDE) systems.