bluuebunny/crossref_metadata_2025_split huggingface dataset:
Morphological Characterization of Decimeter‐ to Hectometer‐Scale Impact Craters at the Chang’E‐3/4/5 Landing Sites
Authors: Li Yueyang , Fa Wenzhe , Jia Bojun 
Published: March 2023

AbstractThe morphology of impact craters on the Moon is important for understanding impact cratering process and lunar surface properties. Though the morphology of lunar impact craters at hectometer scales and larger is extensively investigated and well understood, the morphology of very small craters is rarely studied due to the lack of high‐resolution data. In this study, we investigated the morphology of 1,513 craters at decimeter to hectometer scales using the 5 mm/pixel–0.5 m/pixel topographic data of the Chang’E‐3/4/5 (CE‐3/4/5) landing regions. Our results show that crater depth, rim height, and inner wall slope increase with the diameter and that the mean values of depth/diameter ratio, rim height/diameter ratio, and inner wall slope are 0.065, 0.017, and 10.5°, respectively. These morphometric parameters are smaller than those of large craters above hectometer scales, which is probably due to low‐strength surficial regolith and rapid topographic degradation. The comparison of the morphometric parameters among the three regions suggests that the CE‐4, CE‐3, and CE‐5 landing regions have the highest, intermediate, and lowest regolith strengths, respectively. In addition, we first observed widespread meter‐scale concentric and flat‐bottomed craters in optical images, which are most probably formed due to strength heterogeneity within the regolith layer. Our results can help to understand near‐surface properties of the regolith layer, lunar surface evolution, and impact cratering process in the strength regime.
Ratio of In Situ CO2 to CH4 Production and Its Environmental Controls in Polygonal Tundra Soils of Samoylov Island, Northeastern Siberia
Authors: Galera Leonardo de A. , Eckhardt Tim , Beer Christian , Pfeiffer Eva‐Maria , Knoblauch Christian 
Published: March 2023

AbstractArctic warming causes permafrost thaw and accelerates microbial decomposition of soil organic matter (SOM) to carbon dioxide (CO2) and methane (CH4). The determining factors for the ratio between CO2 and CH4 formation are still not well understood due to scarce in situ measurements, particularly in remote Arctic regions. We quantified the CO2:CH4 ratios of SOM decomposition in wet and dry tundra soils by using CO2 fluxes from clipped plots and in situ CH4 fluxes from vegetated plots. At the water‐saturated site, CO2:CH4 ratios decreased sharply from 95 at beginning of July to about 10 in August and September with a median of 12.2 (7.70–17.1; 25%–75% quartiles) over the whole vegetation period. When considering CH4 oxidation, estimated to reduce in situ CH4 fluxes by 10%–31%, even lower CO2:CH4 ratios were calculated (median 10.9–8.41). Active layer depth and soil temperature were the main factors controlling these ratios. Methane production was associated with subsoil (40 cm) temperature, while heterotrophic respiration was related to topsoil (5 cm) temperatures. As expected, CO2:CH4 ratios were substantially higher at the dry site (median 373, 292–500, 25%–75% quartiles). Both tundra types lost carbon preferentially in form of CO2, and CH4‐C represented only 0.27% of the dry tundra total carbon loss and 6.91% of the wet tundra total carbon loss. The current study demonstrates the dynamic of in situ CO2:CH4 ratios from SOM decomposition and will help improve simulations of future CO2 and CH4 fluxes from thawing tundra soils.
The Study on Modeling of Global Plasmaspheric Hiss Amplitude Based on Deep Learning Algorithm
Authors: Tang Rongxin , Wang Zhenghan , Li Haimeng , Chen Zhou , Ouyang Zhihai , Deng Xiaohua 
Published: March 2023

AbstractPlasmaspheric hiss waves make great significance on the loss of electrons in the Earth's radiation belts. The prediction and reconstruction for global evolution plasmaspheric hiss are critical to investigate the dynamic process of radiation belt. In this study, the realistic variation model of plasmaspheric waves is established based on deep learning technology. Using Light Gradient Boosting Machine and Permutation Importance methods, we first select optimal indices and corresponding historical time series associated with variation of plasmaspheric hiss waves. Then the geomagnetic indices in corresponding time series are considered as input of deep neural network model, and the samples of plasmaspheric hiss waves observed from Van Allen Probe A are utilized for training and validation. The result indicates that the model can roughly reproduce the variation of integrated hiss wave amplitude during geomagnetic storm. Based on the model, we analyze the global evolution of hiss waves during a geomagnetic storm event. In addition, we find that the prediction performance has been greatly improved with the addition of in situ density as an auxiliary input parameter, it provides a new idea of establishing higher accuracy model with auxiliary input of other characteristic parameters.
YBX1 integration of oncogenic PI3K/mTOR signalling regulates the fitness of malignant epithelial cells
Authors: Bai Yuchen , Gotz Carolin , Chincarini Ginevra , Zhao Zixuan , Slaney Clare , Boath Jarryd , Furic Luc , Angel Christopher , Jane Stephen M. , Phillips Wayne A. , Stacker Steven A. , Farah Camile S. , Darido Charbel 
Published: March 2023

AbstractIn heterogeneous head and neck cancer (HNC), subtype-specific treatment regimens are currently missing. An integrated analysis of patient HNC subtypes using single-cell sequencing and proteome profiles reveals an epithelial-mesenchymal transition (EMT) signature within the epithelial cancer-cell population. The EMT signature coincides with PI3K/mTOR inactivation in the mesenchymal subtype. Conversely, the signature is suppressed in epithelial cells of the basal subtype which exhibits hyperactive PI3K/mTOR signalling. We further identify YBX1 phosphorylation, downstream of the PI3K/mTOR pathway, restraining basal-like cancer cell proliferation. In contrast, YBX1 acts as a safeguard against the proliferation-to-invasion switch in mesenchymal-like epithelial cancer cells, and its loss accentuates partial-EMT and in vivo invasion. Interestingly, phospho-YBX1 that is mutually exclusive to partial-EMT, emerges as a prognostic marker for overall patient outcomes. These findings create a unique opportunity to sensitise mesenchymal cancer cells to PI3K/mTOR inhibitors by shifting them towards a basal-like subtype as a promising therapeutic approach against HNC.
Catalyzing next-generation Artificial Intelligence through NeuroAI
Authors: Zador Anthony , Escola Sean , Richards Blake , Ölveczky Bence , Bengio Yoshua , Boahen Kwabena , Botvinick Matthew , Chklovskii Dmitri , Churchland Anne , Clopath Claudia , DiCarlo James , Ganguli Surya , Hawkins Jeff , Körding Konrad , Koulakov Alexei , LeCun Yann , Lillicrap Timothy , Marblestone Adam , Olshausen Bruno , Pouget Alexandre , Savin Cristina , Sejnowski Terrence , Simoncelli Eero , Solla Sara , Sussillo David , Tolias Andreas S. , Tsao Doris 
Published: March 2023

AbstractNeuroscience has long been an essential driver of progress in artificial intelligence (AI). We propose that to accelerate progress in AI, we must invest in fundamental research in NeuroAI. A core component of this is the embodied Turing test, which challenges AI animal models to interact with the sensorimotor world at skill levels akin to their living counterparts. The embodied Turing test shifts the focus from those capabilities like game playing and language that are especially well-developed or uniquely human to those capabilities – inherited from over 500 million years of evolution – that are shared with all animals. Building models that can pass the embodied Turing test will provide a roadmap for the next generation of AI.
Modulation of MRSA virulence gene expression by the wall teichoic acid enzyme TarO
Authors: Lu Yunfu , Chen Feifei , Zhao Qingmin , Cao Qiao , Chen Rongrong , Pan Huiwen , Wang Yanhui , Huang Haixin , Huang Ruimin , Liu Qian , Li Min , Bae Taeok , Liang Haihua , Lan Lefu 
Published: March 2023

AbstractPhenol-soluble modulins (PSMs) and Staphylococcal protein A (SpA) are key virulence determinants for community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA), an important human pathogen that causes a wide range of diseases. Here, using chemical and genetic approaches, we show that inhibition of TarO, the first enzyme in the wall teichoic acid (WTA) biosynthetic pathway, decreases the expression of genes encoding PSMs and SpA in the prototypical CA-MRSA strain USA300 LAC. Mechanistically, these effects are linked to the activation of VraRS two-component system that directly represses the expression of accessory gene regulator (agr) locus and spa. The activation of VraRS was due in part to the loss of the functional integrity of penicillin-binding protein 2 (PBP2) in a PBP2a-dependent manner. TarO inhibition can also activate VraRS in a manner independent of PBP2a. We provide multiple lines of evidence that accumulation of lipid-linked peptidoglycan precursors is a trigger for the activation of VraRS. In sum, our results reveal that WTA biosynthesis plays an important role in the regulation of virulence gene expression in CA-MRSA, underlining TarO as an attractive target for anti-virulence therapy. Our data also suggest that acquisition of PBP2a-encoding mecA gene can impart an additional regulatory layer for the modulation of key signaling pathways in S. aureus.
A Long-term Consistent Artificial Intelligence and Remote Sensing-based Soil Moisture Dataset
Authors: Skulovich Olya , Gentine Pierre 
Published: March 2023

AbstractThe Consistent Artificial Intelligence (AI)-based Soil Moisture (CASM) dataset is a global, consistent, and long-term, remote sensing soil moisture (SM) dataset created using machine learning. It is based on the NASA Soil Moisture Active Passive (SMAP) satellite mission SM data and is aimed at extrapolating SMAP-like quality SM back in time using previous satellite microwave platforms. CASM represents SM in the top soil layer, and it is defined on a global 25 km EASE-2 grid and for 2002–2020 with a 3-day temporal resolution. The seasonal cycle is removed for the neural network training to ensure its skill is targeted at predicting SM extremes. CASM comparison to 367 globalin-situSM monitoring sites shows a SMAP-like median correlation of 0.66. Additionally, the SM product uncertainty was assessed, and both aleatoric and epistemic uncertainties were estimated and included in the dataset. CASM dataset can be used to study a wide range of hydrological, carbon cycle, and energy processes since only a consistent long-term dataset allows assessing changes in water availability and water stress.
Large scale crowdsourced radiotherapy segmentations across a variety of cancer anatomic sites
Authors: Wahid Kareem A. , Lin Diana , Sahin Onur , Cislo Michael , Nelms Benjamin E. , He Renjie , Naser Mohammed A. , Duke Simon , Sherer Michael V. , Christodouleas John P. , Mohamed Abdallah S. R. , Murphy James D. , Fuller Clifton D. , Gillespie Erin F. 
Published: March 2023

AbstractClinician generated segmentation of tumor and healthy tissue regions of interest (ROIs) on medical images is crucial for radiotherapy. However, interobserver segmentation variability has long been considered a significant detriment to the implementation of high-quality and consistent radiotherapy dose delivery. This has prompted the increasing development of automated segmentation approaches. However, extant segmentation datasets typically only provide segmentations generated by a limited number of annotators with varying, and often unspecified, levels of expertise. In this data descriptor, numerous clinician annotators manually generated segmentations for ROIs on computed tomography images across a variety of cancer sites (breast, sarcoma, head and neck, gynecologic, gastrointestinal; one patient per cancer site) for the Contouring Collaborative for Consensus in Radiation Oncology challenge. In total, over 200 annotators (experts and non-experts) contributed using a standardized annotation platform (ProKnow). Subsequently, we converted Digital Imaging and Communications in Medicine data into Neuroimaging Informatics Technology Initiative format with standardized nomenclature for ease of use. In addition, we generated consensus segmentations for experts and non-experts using the Simultaneous Truth and Performance Level Estimation method. These standardized, structured, and easily accessible data are a valuable resource for systematically studying variability in segmentation applications.
Three-dimensional visualization of neural networks inside bone by Osteo-DISCO protocol and alteration of bone remodeling by surgical nerve ablation
Authors: Utagawa Kurando , Shin Takaei , Yamada Hironori , Ochi Hiroki , Sunamura Satoko , Unno Aiko , Akazawa Chihiro , Ema Masatsugu , Takeda Shu , Okawa Atsushi , Sato Shingo 
Published: March 2023

AbstractBone is one of the largest organ systems in humans and is considered to regulate whole-body homeostasis in cooperation with other organs. We have previously reported that a sympathetic or sensory nervous system inside bone regulates bone homeostasis. However, the detailed regulatory mechanism, including the distribution of nerves inside bone, remains unknown. Although a two-dimensional histological analysis has been widely used to evaluate the structure of nerves or blood vessels, the actual structure is more complex, suggesting that it should be evaluated three-dimensionally. Here, we established a novel bone tissue clearing technique (Osteo-DISCO) for murine bones which enabled us to visualize the detailed distribution of nerves or blood vessels inside bone. Interestingly, we found that there is a specific nerve entry site in each long bone and that surgical ablation of the specific nerve fibers entering bone tissue led to decreased bone formation and impaired bone regeneration. Furthermore, we revealed that the administration of calcitonin gene-related peptide (CGRP), which is primarily released from sensory nerves, suppressed the bone loss caused by surgical nerve ablation. An in vitro study also indicated that CGRP directly promotes osteoblast activity, suggesting that sensory nerves inside bone can regulate osteogenesis via the secretion of CGRP.
Offloading operation bivariate extreme response statistics for FPSO vessel
Authors: Gaidai Oleg , Cao Yu , Xu Xiaosen , Xing Yihan 
Published: March 2023

AbstractThe Floating Production Storage and Offloading unit (FPSO) is an offshore unit producing and storing crude oil prior to tanker transport. An important design concern is an accurate prediction of risky dynamic hawser tensions during FPSO offloading operations. Bivariate extreme hawser tension contours are important for selecting proper design values. This paper employed the AQWA hydrodynamic software to analyze vessel hydrodynamic wave loads dynamic response, acting on FPSO vessels under realistic sea state conditions. This paper presents an efficient method for estimating FPSO bivariate response statistics based on numerical simulations validated by various experiments. The bivariate Average Conditional Exceedance Rate (ACER2D) method offers an accurate bivariate extreme value probability distribution and return period contours estimation, utilizing available data efficiently. The two-dimensional probability contours, corresponding to low probability return periods, are easily obtained by the ACER2D method. The performance of the presented method has shown that the ACER2D method provides an efficient and accurate prediction of extreme return period contours. The suggested approach may be used for FPSO vessel design, minimizing potential FPSO hawser damage. Bivariate contours yield bivariate design points, as opposed to a pair of uncoupled univariate design points with the same return period as currently adopted in the industry.
A genome-wide association study identifies a possible role for cannabinoid signalling in the pathogenesis of diabetic kidney disease
Authors: Osman Wael , Mousa Mira , Albreiki Mohammed , Baalfaqih Zahrah , Daggag Hinda , Hill Claire , McKnight Amy Jayne , Maxwell Alexander P. , Al Safar Habiba 
Published: March 2023

AbstractDiabetic kidney disease (DKD), also known as diabetic nephropathy, is the leading cause of renal impairment and end-stage renal disease. Patients with diabetes are at risk for DKD because of poor control of their blood glucose, as well as nonmodifiable risk factors including age, ethnicity, and genetics. This genome-wide association study (GWAS) was conducted for the first time in the Emirati population to investigate possible genetic factors associated with the development and progression of DKD. We included data on 7,921,925 single nucleotide polymorphism (SNPs) in 258 cases of type 2 diabetes mellitus (T2DM) who developed DKD and 938 control subjects with T2DM who did not develop DKD. GWAS suggestive results (P < 1 × 10–5) were further replicated using summary statistics from three cohorts with T2DM-induced DKD (Bio Bank Japan data, UK Biobank, and FinnGen Project data) and T1DM-induced DKD (UK-ROI cohort data from Belfast, UK). When conducting a multiple linear regression model for gene-set analyses, the CNR2 gene demonstrated genome-wide significance at 1.46 × 10–6. SNPs in CNR2 gene, encodes cannabinoid receptor 2 or CB2, were replicated in Japanese samples with the leading SNP rs2501391 showing a Pcombined = 9.3 × 10–7, and odds ratio = 0.67 in association with DKD associated with T2DM, but not with T1DM, without any significant association with T2DM itself. The allele frequencies of our cohort and those of the replication cohorts were in most cases markedly different. In addition, we replicated the association between rs1564939 in the GLRA3 gene and DKD in T2DM (P = 0.016, odds ratio = 0.54 per allele C). Our findings suggest evidence that cannabinoid signalling may be involved in the development of DKD through CB2, which is expressed in different kidney regions and known to be involved in insulin resistance, inflammation, and the development of kidney fibrosis.
Innovative metal oxides (CaO, SrO, MgO) impregnated waste-derived activated carbon for biohydrogen purification
Authors: Koo-amornpattana Wanida , Phadungbut Poomiwat , Kunthakudee Naphaphan , Jonglertjunya Woranart , Ratchahat Sakhon , Hunsom Mali 
Published: March 2023

AbstractIn this work, a series of innovative metal oxide impregnated waste-derived activated carbons (MO/AC) was synthesized and used to purify the simulated biohydrogen based on the concept of CO2 removal from the gas stream. Effects of metal oxide types (CaO, SrO and MgO) and contents of the best metal oxides on the morphology and the CO2 adsorption capacity from the biohydrogen were investigated. It was found that both metal oxide types and contents played an important role on the adsorbent textural property and surface chemistry as well as the CO2 adsorption capacity. Among all synthesized adsorbent, the MgO-impregnated AC with 12 wt.% MgO (12MgO/AC) exhibited the highest CO2 adsorption capacity of around 94.02 mg/g. With this successive adsorbent, the biohydrogen with the H2 purity higher than 90 mol% can be achieved from the gas stream with 50 mol% CO2 for the first 2 min of adsorption period in a fixed bed reactor. The mechanism of CO2 adsorption occurred via a combined process of the physisorption and chemisorption. Besides, the 12MgO/AC exhibited a high recyclability after several repetitive adsorption/desorption cycles.
A computational fluid dynamics analysis on Fe3O4–H2O based nanofluid axisymmetric flow over a rotating disk with heat transfer enhancement
Authors: Farooq Umar , Hassan Ali , Fatima Nahid , Imran Muhammad , Alqurashi M. S. , Noreen Sobia , Akgül Ali , Bariq Abdul 
Published: March 2023

AbstractIn present times modern electronic devices often come across thermal difficulties as an outcome of excessive heat production or reduction in surface area for heat exclusion. The current study is aimed to inspect the role of iron (III) oxide in heat transfer enhancement over the rotating disk in an axisymmetric flow. Water is utilized as base fluid conveying nano-particle over the revolving axisymmetric flow mechanism. Additionally, the computational fluid dynamics (CFD) approach is taken into consideration to design and compute the present problem. For our convenience, two-dimensional axisymmetric flow configurations are considered to illustrate the different flow profiles. For radial, axial, and tangential velocity profiles, the magnitude of the velocity, streamlines, and surface graphs are evaluated with the similarity solution in the computational fluid dynamics module. The solution of dimensionless equations and the outcomes of direct simulations in the CFD module show a comparable solution of the velocity profile. It is observed that with an increment in nanoparticle volumetric concentration the radial velocity decline where a tangential motion of flow enhances. Streamlines stretch around the circular surface with the passage of time. The high magnetization force$$0 \le {{\mathrm{m}}_{1}}\le 6$$0≤m1≤6resist the free motion of the nanofluid around the rotating disk. Such research has never been done, to the best of the researchers’ knowledge. The outcomes of this numerical analysis could be used for the design, control, and optimization of numerous thermal engineering systems, as described above, due to the intricate physics of nanofluid under the influences of magnetic field and the inclusion of complex geometry. Ferrofluids are metallic nanoparticle colloidal solutions. These kinds of fluids do not exist in nature. Depending on their purpose, ferrofluids are produced using a variety of processes. One of the most essential characteristics of ferrofluids is that they operate in a zero-gravity environment. Ferrofluids have a wide range of uses in engineering and medicine. Ferrofluids have several uses, including heat control loudspeakers and frictionless sealing. In the sphere of medicine, however, ferrofluid is employed in the treatment of cancer via magneto hyperthermia.
Influence of nanoparticles aggregation and Lorentz force on the dynamics of water-titanium dioxide nanoparticles on a rotating surface using finite element simulation
Authors: Ali Bagh , Siddique Imran , Ahmad Hijaz , Askar Sameh 
Published: March 2023

AbstractThis communication briefings the roles of Lorentz force and nanoparticles aggregation on the characteristics of water subject to Titanium dioxide rotating nanofluid flow toward a stretched surface. Due to upgrade the thermal transportation, the nanoparticles are incorporated, which are play significance role in modern technology, electronics, and heat exchangers. The primary objective of this communication is to observe the significance of nanoparticles aggregation to enhance the host fluid thermal conductivity. In order to model our work and investigate how aggregation characteristics affect the system’s thermal conductivity, aggregation kinetics at the molecular level has been mathematically introduced. A dimensionless system of partial-differential equations is produced when the similarity transform is applied to a elaborated mathematical formulation. Thereafter, the numerical solution is obtained through a well-known computational finite element scheme via MATLAB environment. When the formulation of nanoparticle aggregation is taken into consideration, it is evident that although the magnitude of axial and transverse velocities is lower, the temperature distribution is enhanced by aggregation.