bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesis and morphological characterization of CaSO$$_{4}$$: low-temperature Raman spectroscopy analysis of vibrational modes
Authors: Raba-Páez A. M. , Barba-Ortega J. , Joya M. R. 
Published: June 2024

AbstractThis study delves into the synthesis of CaSO$$_{4}$$

4

materials using the Pechini and sol-gel methods, followed by heat treatment up to 900 $$^{\circ }$$

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C. X-ray analysis discerned distinct phases, with one method yielding pure orthorhombic anhydrite and the other predominantly producing a mixture of orthorhombic anhydrite and bassanite. Scanning electron microscopy (SEM) showcased homogeneous columnar morphologies for the anhydrite samples and irregularly sized particles for the alternative method. Photoluminescence (PL) measurements demonstrated emissions in the visible range (approximately 400 nm to 700 nm) with differences noted between synthesis methods. Low-temperature Raman spectroscopy (20 K to room temperature) unveiled unique vibrational modes, notably with the orthorhombic phase of anhydrite exhibiting the most intense peak at 1017 cm$$^{-1}$$

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1

. These powders, intended for thin film applications, bear significance in electronics, optoelectronics, and nanotechnology. A thorough comprehension of their structural and vibrational properties at the microscopic level is paramount for material and device design and optimization.
Modelling the determinants for sustainable smart city through interpretive structure modelling and analytic hierarchy process
Authors: Singh Shailee , Kumar Virender 
Published: June 2024

AbstractRapid increasing urbanization and resource scarcity are global phenomena nowadays, leading to the urban transformation of cities into smart cities. This article explores sustainability by using the lens of the spirit of place (SOP) for smart city development by proposing a model for the transformation of the cities into smart cities and attainment of the sustainable development simultaneously based on Interpretive Structure Modelling (ISM) and Analytic Hierarchy Process (AHP). This study followed a systematic approach by utilizing an analytical framework that included an extensive literature review and urban experts' opinions for the identification of a pool of indicators and its evaluation for validity, pilot testing, and administration of a questionnaire to a population sample. The study utilizes a sample of 142 participants who have witnessed the transformation of their city over the years. The research showed that every place has its own identity known to be the ‘spirit of place’ that helps in assessing the sustainable characteristics and utilizing that in the path of planning and development for the attainment of sustainable development. It also showed that urban developers should consider local populations’ views and important aspects in designing and planning development projects to achieve sustainable development with resilient infrastructure. This study will help facilitate sustainability at a local level for urban developers, planners, and decision-makers while crafting strategic plans.
Data‐Driven Investigation Reveals Subaerial Proportion of Basalts Since the Early Archean
Authors: Liu Chun‐Tao , Liu Xiao‐Ming , ZhangZhou J. 
Published: June 2024

AbstractThe subaerial exposure of the modern continental crust through time remains intensely debated, with estimates of the first exposure ranging from the late Archean to the Neoproterozoic. To constrain when and how much of the continental crust was exposed subaerially during Earth's history, we trained a supervised machine learning model on the compositions of modern subaerial and submerged basalts. Then, we applied this well‐trained model to a refined worldwide data set of basaltic compositions and calculated the mean proportions of basalts erupted subaerially since 3.8 billion years ago (Ga). Our results suggest that ∼20% of the basalts were exposed subaerially in the early Archean, which may have driven the synthesis of biopolymers crucial to the origins and evolution of life. The proportion of subaerial basalts increased markedly during two stages between the late Archean and the Paleoproterozoic before reaching the present‐day level no earlier than ∼1.8 Ga.
Spatio‐Temporal Machine Learning for Regional to Continental Scale Terrestrial Hydrology
Authors: Bennett Andrew , Tran Hoang , De la Fuente Luis , Triplett Amanda , Ma Yueling , Melchior Peter , Maxwell Reed M. , Condon Laura E. 
Published: June 2024

AbstractIntegrated hydrologic models can simulate coupled surface and subsurface processes but are computationally expensive to run at high resolutions over large domains. Here we develop a novel deep learning model to emulate subsurface flows simulated by the integrated ParFlow‐CLM model across the contiguous US. We compare convolutional neural networks like ResNet and UNet run autoregressively against our novel architecture called the Forced SpatioTemporal RNN (FSTR). The FSTR model incorporates separate encoding of initial conditions, static parameters, and meteorological forcings, which are fused in a recurrent loop to produce spatiotemporal predictions of groundwater. We evaluate the model architectures on their ability to reproduce 4D pressure heads, water table depths, and surface soil moisture over the contiguous US at 1 km resolution and daily time steps over the course of a full water year. The FSTR model shows superior performance to the baseline models, producing stable simulations that capture both seasonal and event‐scale dynamics across a wide array of hydroclimatic regimes. The emulators provide over 1,000× speedup compared to the original physical model, which will enable new capabilities like uncertainty quantification and data assimilation for integrated hydrologic modeling that were not previously possible. Our results demonstrate the promise of using specialized deep learning architectures like FSTR for emulating complex process‐based models without sacrificing fidelity.
Long‐Term Trends in Productivity Across Intermountain West Lakes Provide No Evidence of Widespread Eutrophication
Authors: Sillen Samuel J. , Ross Matthew R. V. , Collins Sarah M. 
Published: June 2024

AbstractEutrophication represents a major threat to freshwater systems and climate change is expected to drive further increases in freshwater primary productivity. However, long‐term in situ data is available for very few lakes and makes identifying trends and drivers of eutrophication challenging. Using remote sensing data, we conducted a retrospective analysis of long‐term trends in trophic status among lakes greater than 10 ha across the Intermountain West, a region with understudied water quality trends and limited long‐term data sets. We found that most lakes (55%) were not exhibiting shifts in trophic status from 1984 to 2019. Our results also show that increases in eutrophication were rare (3% of lakes) during this period, and that lakes becoming increasingly oligotrophic were more common (17% of lakes). Lakes that were not trending occupied a wide range of lake and landscape characteristics, whereas lakes that were becoming more oligotrophic tended to have larger residence times and were located in catchments with greater clay content and more development. Our results highlight that while there are well‐established narratives that climate change can lead to more eutrophication of lakes, this is not broadly observed in our data set, where we found more lakes in the Intermountain West becoming more oligotrophic than lakes becoming eutrophic.
Sea Ice Deformation Is Not Scale Invariant Over Length Scales Greater Than a Kilometer
Authors: Hutchings Jennifer K. , Bliss Angela C. , Mondal Dhiman , Elosegui Pedro 
Published: June 2024

AbstractIn March and April 2021, buoys were deployed in the Beaufort Sea, Arctic Ocean, to measure sea‐ice horizontal deformation over spatial scales that had not been previously achieved. Geodetic‐quality position measurements allowed measurements of strain‐rate over lengths from about 200 m to 2 km. Conventional ice‐drifters extended spatial coverage up to about 100 km. Past studies find there is multi‐fractal behavior for horizontal sea‐ice deformation from 10 to 1,000 km. Our results demonstrate that such behavior does not hold when including spatial scales below 10 km. We find that sea‐ice deformation is not scale invariant between the scale of individual sea‐ice floes and aggregates of floes. Therefore, we cannot expect the same physical laws or forcing to describe sea‐ice kinematics over these regimes, nor can we assume log‐log linear behavior for mean deformation. Using this scaling behavior as a metric to validate models that resolve sea ice floes and their interactions is hence not recommended.
Canonical and non-canonical functions of p53 isoforms: potentiating the complexity of tumor development and therapy resistance
Authors: Guo Yitian , Wu Hang , Wiesmüller Lisa , Chen Ming 
Published: June 2024

AbstractFull-length p53 (p53α) plays a pivotal role in maintaining genomic integrity and preventing tumor development. Over the years, p53 was found to exist in various isoforms, which are generated through alternative splicing, alternative initiation of translation, and internal ribosome entry site. p53 isoforms, either C-terminally altered or N-terminally truncated, exhibit distinct biological roles compared to p53α, and have significant implications for tumor development and therapy resistance. Due to a lack of part and/or complete C- or N-terminal domains, ectopic expression of some p53 isoforms failed to induce expression of canonical transcriptional targets of p53α like CDKN1A or MDM2, even though they may bind their promoters. Yet, p53 isoforms like Δ40p53α still activate subsets of targets including MDM2 and BAX. Furthermore, certain p53 isoforms transactivate even novel targets compared to p53α. More recently, non-canonical functions of p53α in DNA repair and of different isoforms in DNA replication unrelated to transcriptional activities were discovered, amplifying the potential of p53 as a master regulator of physiological and tumor suppressor functions in human cells. Both regarding canonical and non-canonical functions, alternative p53 isoforms frequently exert dominant negative effects on p53α and its partners, which is modified by the relative isoform levels. Underlying mechanisms include hetero-oligomerization, changes in subcellular localization, and aggregation. These processes ultimately influence the net activities of p53α and give rise to diverse cellular outcomes. Biological roles of p53 isoforms have implications for tumor development and cancer therapy resistance. Dysregulated expression of isoforms has been observed in various cancer types and is associated with different clinical outcomes. In conclusion, p53 isoforms have expanded our understanding of the complex regulatory network involving p53 in tumors. Unraveling the mechanisms underlying the biological roles of p53 isoforms provides new avenues for studies aiming at a better understanding of tumor development and developing therapeutic interventions to overcome resistance.
Allele frequency of pathogenic variants causing acid sphingomyelinase deficiency and Gaucher disease in the general Japanese population
Authors: Sako Shuhei , Oishi Kimihiko , Ida Hiroyuki , Imagawa Eri 
Published: June 2024

Abstract
Acid sphingomyelinase deficiency (ASMD) and Gaucher disease (GD) are lysosomal storage disorders associated with hepatosplenomegaly and thrombocytopenia. The incidences of ASMD and GD are known to be particularly high in the Ashkenazi Jewish population. Conversely, the number of reported patients with these diseases has been limited in Asian countries, including Japan. Here, we reviewed the allele frequencies of pathogenic variants causing ASMD and GD in the Japanese population and populations with various ancestry backgrounds using the Japanese Multi-Omics Reference Panel 54KJPN and the Genome Aggregation Database v4.0.0. The estimated carrier frequencies of ASMD- and GD-related variants were 1/180 and 1/154 in Japanese individuals, equivalent to disease occurrence frequencies of 1/128,191 and 1/94,791 individuals, respectively. These frequencies are much higher than previously expected. Our data also suggest that there are more patients with a milder form of ASMD and nonspecific clinical findings who have not yet been diagnosed.
Multispecies-coadsorption-induced rapid preparation of graphene glass fiber fabric and applications in flexible pressure sensor
Authors: Wang Kun , Sun Xiucai , Cheng Shuting , Cheng Yi , Huang Kewen , Liu Ruojuan , Yuan Hao , Li Wenjuan , Liang Fushun , Yang Yuyao , Yang Fan , Zheng Kangyi , Liang Zhiwei , Tu Ce , Liu Mengxiong , Ma Mingyang , Ge Yunsong , Jian Muqiang , Yin Wanjian , Qi Yue , Liu Zhongfan 
Published: June 2024

AbstractDirect chemical vapor deposition (CVD) growth of graphene on dielectric/insulating materials is a promising strategy for subsequent transfer-free applications of graphene. However, graphene growth on noncatalytic substrates is faced with thorny issues, especially the limited growth rate, which severely hinders mass production and practical applications. Herein, graphene glass fiber fabric (GGFF) is developed by graphene CVD growth on glass fiber fabric. Dichloromethane is applied as a carbon precursor to accelerate graphene growth, which has a low decomposition energy barrier, and more importantly, the produced high-electronegativity Cl radical can enhance adsorption of active carbon species by Cl–CH2 coadsorption and facilitate H detachment from graphene edges. Consequently, the growth rate is increased by ~3 orders of magnitude and carbon utilization by ~960-fold, compared with conventional methane precursor. The advantageous hierarchical conductive configuration of lightweight, flexible GGFF makes it an ultrasensitive pressure sensor for human motion and physiological monitoring, such as pulse and vocal signals.
Direct production of low-oxygen-concentration titanium from molten titanium
Authors: Okabe Toru H. , Kamimura Gen , Ikeda Takashi , Ouchi Takanari 
Published: June 2024

AbstractTitanium (Ti) is an attractive material, abundant in nature and possessing superior mechanical and chemical properties. However, its widespread use is significantly hampered by the strong affinity between titanium and oxygen (O), resulting in elevated manufacturing costs during the refining, melting, and casting processes. The current work introduces a high-throughput technique that effectively reduces the oxygen content in molten titanium to a level suitable for structural material applications (1000 mass ppm, equivalent to 0.1 mass%). This technique aspires to streamline the mass production of titanium by seamlessly integrating the refining, melting, and casting processes. The developed method leverages the high affinity of rare-earth metals, such as yttrium (Y), for oxygen. This method utilizes the formation reaction of their oxyhalides (YOF) to directly remove oxygen from liquid titanium, resulting in titanium with a significantly reduced oxygen content of 200 mass ppm. This technique enables the direct conversion of titanium oxide feeds into low-oxygen titanium without requiring conversion into intermediate compounds. Additionally, this process offers a pathway for the upgrade recycling of high-oxygen-content titanium scrap directly into low-oxygen titanium. Consequently, this technology holds the potential to dramatically lower titanium production costs, thereby facilitating its more widespread utilization.
Ferroptosis induction in host rice by endophyte OsiSh-2 is necessary for mutualism and disease resistance in symbiosis
Authors: Xiong Xianqiu , Zeng Jing , Ning Qing , Liu Heqin , Bu Zhigang , Zhang Xuan , Zeng Jiarui , Zhuo Rui , Cui Kunpeng , Qin Ziwei , Gao Yan , Liu Xuanming , Zhu Yonghua 
Published: June 2024

AbstractFerroptosis is an iron-dependent cell death that was discovered recently. For beneficial microbes to establish mutualistic relationships with hosts, precisely controlled cell death in plant cells is necessary. However, whether ferroptosis is involved in the endophyte‒plant system is poorly understood. Here, we reported that endophytic Streptomyces hygroscopicus OsiSh-2, which established a sophisticated and beneficial interaction with host rice plants, caused ferroptotic cell death in rice characterized by ferroptosis- and immune-related markers. Treatments with ferroptosis inhibitors and inducers, different doses of OsiSh-2, and the siderophore synthesis-deficient mutant ΔcchH revealed that only moderate ferroptosis induced by endophytes is essential for the establishment of an optimal symbiont to enhance plant growth. Additionally, ferroptosis involved in a defence-primed state in rice, which contributed to improved resistance against rice blast disease. Overall, our study provides new insights into the mechanisms of endophyte‒plant interactions mediated by ferroptosis and suggests new directions for crop yield promotion.
Enhancing the diagnosis of functionally relevant coronary artery disease with machine learning
Authors: Bock Christian , Walter Joan Elias , Rieck Bastian , Strebel Ivo , Rumora Klara , Schaefer Ibrahim , Zellweger Michael J. , Borgwardt Karsten , Müller Christian 
Published: June 2024

AbstractFunctionally relevant coronary artery disease (fCAD) can result in premature death or nonfatal acute myocardial infarction. Its early detection is a fundamentally important task in medicine. Classical detection approaches suffer from limited diagnostic accuracy or expose patients to possibly harmful radiation. Here we show how machine learning (ML) can outperform cardiologists in predicting the presence of stress-induced fCAD in terms of area under the receiver operating characteristic (AUROC: 0.71 vs. 0.64, p = 4.0E-13). We present two ML approaches, the first using eight static clinical variables, whereas the second leverages electrocardiogram signals from exercise stress testing. At a target post-test probability for fCAD of <15%, ML facilitates a potential reduction of imaging procedures by 15–17% compared to the cardiologist’s judgement. Predictive performance is validated on an internal temporal data split as well as externally. We also show that combining clinical judgement with conventional ML and deep learning using logistic regression results in a mean AUROC of 0.74.
Uncertainty-aware particle segmentation for electron microscopy at varied length scales
Authors: Rettenberger Luca , Szymanski Nathan J. , Zeng Yan , Schuetzke Jan , Wang Shilong , Ceder Gerbrand , Reischl Markus 
Published: June 2024

AbstractElectron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron scale. To study the powder samples that are widely used in materials development, scanning electron microscopes (SEMs) are increasingly used at the laboratory scale to generate large datasets with hundreds of images. Parsing these images to identify distinct particles and determine their morphology requires careful analysis, and automating this process remains challenging. In this work, we enhance the Mask R-CNN architecture to develop a method for automated segmentation of particles in SEM images. We address several challenges inherent to measurements, such as image blur and particle agglomeration. Moreover, our method accounts for prediction uncertainty when such issues prevent accurate segmentation of a particle. Recognizing that disparate length scales are often present in large datasets, we use this framework to create two models that are separately trained to handle images obtained at low or high magnification. By testing these models on a variety of inorganic samples, our approach to particle segmentation surpasses an established automated segmentation method and yields comparable results to the predictions of three domain experts, revealing comparable accuracy while requiring a fraction of the time. These findings highlight the potential of deep learning in advancing autonomous workflows for materials characterization.
A dataset of human capital-weighted population estimates for 185 countries from 1970 to 2100
Authors: Marois Guillaume , Cuaresma Jesus Crespo , Zellmann Jakob , Reiter Claudia 
Published: June 2024

AbstractWe provide a novel dataset of human capital-weighted population size (HCWP) for 185 countries from 1970 to 2100. HCWP summarizes a population’s productive capacity and human capital heterogeneity in a single metric, enabling comparisons across countries and over time. The weights are derived from Mincerian earnings functions applied to multi-country census data on educational attainment. The model used to compute the returns to schooling accounts for the diminishing positive relative relationship between education and wages as the overall education of populations rises. The population weights are adjusted by a skills assessment factor representing differences in education quality across countries and years. HCWP is calculated by applying these adjusted human capital weights to population estimates and projections disaggregated by age, sex and education, spanning the period 1970–2020 and 2020–2100 for five Shared Socioeconomic Pathway scenarios. Validation analyses demonstrate the utility of the new HCWP data in explaining national income trends. As a more comprehensive population measure than basic size and age-sex indicators, HCWP enhances the power of statistical models aimed at the assessment of socioeconomic change impacts and forecasting.
Organoclay-assisted disperse dyeing of polypropylene nanocomposite fabrics in supercritical carbon dioxide
Authors: Elmaaty Tarek A. , Mousa Abdalla A. , Farouk Reham , Elsisi Hanan , Sorour Heba , Youssef Yehya A. , Abbas Dina 
Published: June 2024

AbstractDyeing using supercritical carbon dioxide (SC-CO2) is carried out on the polypropylene (PP) nanocomposite fabrics with model disperse dye compared with their regular fabric at various dyeing temperatures and pressures. The results are compared with those obtained in aqueous dyeing method. The PP nanocompsite fabrics dyed in SC-CO2 medium exhibited higher colour strength (K/S) values compared with their PP regular fabric. The PP nanocompsite fabrics and their regular fabric dyed in SC-CO2 medium have higher K/S values than those dyed in aqueous medium. The color coordinates of all PP fabrics dyed in SC-CO2 and aqueous medium were positive with respect to a* and b* coordinates depending on the disperse red dye uptake. The PP nanocomposite fabrics dyed in SC-CO2 and aqueous medium exhibited higher antibacterial properties than their regular fabrics. All PP fabrics dyed in SC-CO2 and aqueous medium present very good washing, perspiration and light fastness.