bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transfer Learning Aurora Image Classification and Magnetic Disturbance Evaluation
Authors: Sado P. , Clausen L. B. N. , Miloch W. J. , Nickisch H. 
Published: December 2021

AbstractWe develop an open source algorithm to apply Transfer learning to Aurora image classification and Magnetic disturbance Evaluation (TAME). For this purpose, we evaluate the performance of 80 pretrained neural networks using the Oslo Auroral THEMIS (OATH) data set of all‐sky images, both in terms of runtime and their features' predictive capability. From the features extracted by the best network, we retrain the last neural network layer using the Support Vector Machine (SVM) algorithm to distinguish between the labels “arc,” “diffuse,” “discrete,” “cloud,” “moon” and “clear sky/ no aurora”. This transfer learning approach yields 73% accuracy in the six classes; if we aggregate the 3 auroral and 3 non‐aurora classes, we achieve up to 91% accuracy. We apply our classifier to a new dataset of 550,000 images and evaluate the classifier based on these previously unseen images. To show the potential usefulness of our feature extractor and classifier, we investigate two test cases: First, we compare our predictions for the “cloudy” images to meteorological data and second we train a linear ridge model to predict perturbations in Earth's locally measured magnetic field. We demonstrate that the classifier can be used as a filter to remove cloudy images from datasets and that the extracted features allow to predict magnetometer measurements. All procedures and algorithms used in this study are publicly available, and the code and classifier are provided, which opens possibility for large scale studies of all‐sky images.
Massive Multi‐Mission Statistical Study and Analytical Modeling of the Earth's Magnetopause: 2. Shape and Location
Authors: Nguyen G. , Aunai N. , Michotte de Welle B. , Jeandet A. , Lavraud B. , Fontaine D. 
Published: December 2021

AbstractThe Earth magnetopause is the boundary between the magnetosphere and the shocked solar wind. Its location and shape are primarily determined by the properties of the solar wind and interplanetary magnetic field (IMF) but the nature of the control parameters and to what extent they impact the stand‐off distance, the flaring, and the symmetries, on the dayside and night side, is still not well known. We present a large statistical study of the magnetopause location and shape based an extensive multi‐mission magnetopause database, cumulating 17,230 crossings on 17 different spacecraft, from the dayside to lunar nightside distances. The results confirm the power‐law dependency of the stand‐off position on the solar wind pressure. The IMF clock angle itself (all amplitudes combined) does not impact the stand‐off distance, nor does the cone angle. However, the magnetopause is found to move Earthward as the IMF gets stronger and more southward. All upstream conditions combined, it is found that the function used at the root of several analytical models still holds at lunar distances. We find that the equatorial flaring is larger than the meridional one. However, the meridional flaring is found to depend on the seasonal tilt conditions, being larger in the summer hemisphere. The flaring is also found to depend on the IMF clock angle. Meridional flaring increases as the IMF turns south and is then larger than the equatorial flaring. The equatorial flaring barely changes or weakly increases as the IMF turns northward, and is larger than the meridional flaring for northward conditions. The results of the study pave the way for the elaboration of a new analytical empirical expression of the magnetopause location and shape.
Asymmetrically Varying Guide Field During Magnetic Reconnection: Particle‐In‐Cell Simulations
Authors: Spinnangr Susanne F. , Tenfjord Paul , Hesse Michael , Norgren Cecilia , Kolstø Håkon M. , Kwagala Norah K. , Jørgensen Therese Moretto , Pérez‐Coll Jiménez Judit 
Published: December 2021

AbstractUsing fully kinetic particle‐in‐cell modeling, we investigate how magnetic reconnection responds to a varying guide field in one of the inflow regions. We find that the reconnection rate varies significantly when the orientation of the magnetic field changes between being strictly antiparallel and having a guide field. These variations are fairly consistent with the scaling relation for asymmetric reconnection developed by Cassak and Shay (2007). However, the rate is also found to be nonlinearly modulated by changes in the ion inflow velocity. The spatio‐temporal change in the inflow velocity arises as the magnetic forces reconfigure to regions of different magnetic field strengths. The variations in the inflow magnetic field configuration allow for different gradients in the magnetic field, leading to asymmetries in the magnetic tension force. By momentum conservation, this facilitates asymmetries in the inflow velocity, which in turn affects the flux transport into the reconnection site. The outflow is found to be less laminar when the inflow varies, and various signatures of the inflow variations are identified in the outflow.
Insights Into Hydraulic Fracture Growth Gained From a Joint Analysis of Seismometer‐Derived Tilt Signals and Acoustic Emissions
Authors: Niemz P. , Dahm T. , Milkereit C. , Cesca S. , Petersen G. , Zang A. 
Published: December 2021

AbstractHydraulic fracturing is performed to enhance rock permeability, for example, in the frame of geothermal energy production or shale gas exploitation, and can potentially trigger induced seismicity. The tracking of increased permeabilities and the fracturing extent is often based on the microseismic event distribution within the stimulated rock volume, but it is debated whether the microseismic activity adequately depicts the fracture formation. We are able to record tilt signals that appear as long‐period transients (180 s) on two broadband seismometers installed close (17–72 m) to newly formed, meter‐scale hydraulic fractures. With this observation, we can overcome the limitations of the microseismic monitoring alone and verify the fracture mapping. Our analysis for the first time combines a catalog of previously analyzed acoustic emissions ([AEs] durations of 20 ms), indirectly mapping the fractures, with unique tilt signals, that provide independent, direct insights into the deformation of the rock. The analysis allows to identify different phases of the fracturing process including the (re)opening, growth, and aftergrowth of fractures. Further, it helps to differentiate between the formation of complex fracture networks and single macrofractures, and it validates the AE fracture mapping. Our findings contribute to a better understanding of the fracturing processes, which may help to reduce fluid‐injection‐induced seismicity and validate efficient fracture formation.
Type‐Dependent Impact of Aerosols on Precipitation Associated With Deep Convective Cloud Over East Asia
Authors: Han Xinlei , Zhao Bin , Lin Yun , Chen Qixiang , Shi Hongrong , Jiang Zhe , Fan Xuehua , Wang Jiandong , Liou Kuo‐Nan , Gu Yu 
Published: December 2021

AbstractAerosol‐cloud‐precipitation interactions represent one of the most significant uncertainties in climate simulation and projection. In particular, the impact of aerosols on precipitation is highly uncertain due to limited and conflicting observational evidence. A major challenge is to distinguish the effects of different types of aerosols on precipitation associated with deep convective clouds, which produces most of the precipitation in East Asia. Here, we use 9‐yr observations from multiple satellite‐borne sensors and find that the occurrent frequency of heavy rain increases while that of light rain decreases with the increase of aerosol optical depth (AOD) for dust and polluted continental aerosol types. For average hourly precipitation amount, elevated smoke tends to suppress deep convective precipitation, while dust and polluted continental aerosols enhance precipitation mainly through the invigoration of deep convection. The invigoration effect is more significant for clouds with higher cloud base temperature (CBT), while no significant invigoration is observed when CBT is <12°C. A great contrast is found for the response of average hourly precipitation amount to aerosols over ocean and land. While the prevailing continental aerosol types other than smoke increase precipitation, the marine aerosols first enhance and then inhibit precipitation with the increase of AOD. Moreover, our analysis indicates that the above‐mentioned enhancement and inhibition effects on precipitation are mainly caused by aerosols themselves, rather than by the covariation of meteorological factors. These observed relationships between different aerosol types and precipitation frequency and amount provide valuable constraints on the model forecasting of precipitation.
Evidence From Galactic Cosmic Rays That the Sun Has Likely Entered a Secular Minimum in Solar Activity
Authors: Rahmanifard F. , Jordan A. P. , de Wet W. C. , Schwadron N. A. , Wilson J. K. , Owens M. J. , Spence H. E. , Riley P. 
Published: December 2021

AbstractSince the beginning of the space age, the Sun has been in a multi‐cycle period of elevated activity (secular maximum). This secular maximum is the longest in the last 9300 years. Since the end of solar cycle 21 (SC21), however, the Sun has shown a decline in overall activity, which has remarkably increased the fluxes of galactic cosmic rays (GCRs). Here, we investigate the correlation between the modulation of GCRs, the heliospheric magnetic field, and solar wind speed for the last 24 solar cycles to find trends that can potentially be used to predict future solar activity. Specifically, we develop a tool for predicting future magnetic field intensity, based on the hysteresis in the GCR variation, during the last phases of the current cycle. This method estimates that SC25 will be as weak as or weaker than SC24. This would mean that the Sun has likely entered a secular minimum, which, according to historical records, should last for another two cycles (SC25 and SC26).
COVID-19 induces new-onset insulin resistance and lipid metabolic dysregulation via regulation of secreted metabolic factors
Authors: He Xi , Liu Chenshu , Peng Jiangyun , Li Zilun , Li Fang , Wang Jian , Hu Ao , Peng Meixiu , Huang Kan , Fan Dongxiao , Li Na , Zhang Fuchun , Cai Weiping , Tan Xinghua , Hu Zhongwei , Deng Xilong , Li Yueping , Mo Xiaoneng , Li Linghua , Shi Yaling , Yang Li , Zhu Yuanyuan , Wu Yanrong , Liang Huichao , Liao Baolin , Hong Wenxin , He Ruiying , Li Jiaojiao , Guo Pengle , Zhuo Youguang , Zhao Lingzhai , Hu Fengyu , Li Wenxue , Zhu Wei , Zhang Zefeng , Guo Zeling , Zhang Wei , Hong Xiqiang , Cai Weikang , Gu Lei , Du Ziming , Zhang Yang , Xu Jin , Zuo Tao , Deng Kai , Yan Li , Chen Xinwen , Chen Sifan , Lei Chunliang 
Published: December 2021

AbstractAbnormal glucose and lipid metabolism in COVID-19 patients were recently reported with unclear mechanism. In this study, we retrospectively investigated a cohort of COVID-19 patients without pre-existing metabolic-related diseases, and found new-onset insulin resistance, hyperglycemia, and decreased HDL-C in these patients. Mechanistically, SARS-CoV-2 infection increased the expression of RE1-silencing transcription factor (REST), which modulated the expression of secreted metabolic factors including myeloperoxidase, apelin, and myostatin at the transcriptional level, resulting in the perturbation of glucose and lipid metabolism. Furthermore, several lipids, including (±)5-HETE, (±)12-HETE, propionic acid, and isobutyric acid were identified as the potential biomarkers of COVID-19-induced metabolic dysregulation, especially in insulin resistance. Taken together, our study revealed insulin resistance as the direct cause of hyperglycemia upon COVID-19, and further illustrated the underlying mechanisms, providing potential therapeutic targets for COVID-19-induced metabolic complications.
Global predictors of language endangerment and the future of linguistic diversity
Authors: Bromham Lindell , Dinnage Russell , Skirgård Hedvig , Ritchie Andrew , Cardillo Marcel , Meakins Felicity , Greenhill Simon , Hua Xia 
Published: December 2021

AbstractLanguage diversity is under threat. While each language is subject to specific social, demographic and political pressures, there may also be common threatening processes. We use an analysis of 6,511 spoken languages with 51 predictor variables spanning aspects of population, documentation, legal recognition, education policy, socioeconomic indicators and environmental features to show that, counter to common perception, contact with other languages per se is not a driver of language loss. However, greater road density, which may encourage population movement, is associated with increased endangerment. Higher average years of schooling is also associated with greater endangerment, evidence that formal education can contribute to loss of language diversity. Without intervention, language loss could triple within 40 years, with at least one language lost per month. To avoid the loss of over 1,500 languages by the end of the century, urgent investment is needed in language documentation, bilingual education programmes and other community-based programmes.
Global controls on phosphatization of fossils during the Toarcian Oceanic Anoxic Event
Authors: Sinha Sinjini , Muscente A. D. , Schiffbauer James D. , Williams Matt , Schweigert Günter , Martindale Rowan C. 
Published: December 2021

AbstractKonservat-Lagerstätten—deposits with exceptionally preserved fossils—vary in abundance across geographic and stratigraphic space due to paleoenvironmental heterogeneity. While oceanic anoxic events (OAEs) may have promoted preservation of marine lagerstätten, the environmental controls on their taphonomy remain unclear. Here, we provide new data on the mineralization of fossils in three Lower Jurassic Lagerstätten—Strawberry Bank (UK), Ya Ha Tinda (Canada), and Posidonia Shale (Germany) —and test the hypothesis that they were preserved under similar conditions. Biostratigraphy indicates that all three Lagerstätten were deposited during the Toarcian OAE (TOAE), and scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) show that each deposit contains a variety of taxa preserved as phosphatized skeletons and tissues. Thus, despite their geographic and paleoenvironmental differences, all of these Lagerstätten were deposited in settings conducive to phosphatization, indicating that the TOAE fostered exceptional preservation in marine settings around the world. Phosphatization may have been fueled by phosphate delivery from climatically-driven sea level change and continental weathering, with anoxic basins acting as phosphorus traps.
Association of dyslipidemia, diabetes and metabolic syndrome with serum ferritin levels: a middle eastern population-based cross-sectional study
Authors: Al Akl Neyla S. , Khalifa Olfa , Errafii Khaoula , Arredouani Abdelilah 
Published: December 2021

AbstractElevated serum ferritin (SFer) levels are implicated in many energy metabolism abnormalities. The association between SFer levels and metabolic disorders has not been studied in Middle Eastern populations. We aimed at exploring the association between SFer levels and serum lipids, diabetes determinants, and metabolic syndrome in a sample of Qatari adults. This study used biochemical parameters obtained from 1928 participants from the Qatar Biobank cohort. We utilized adjusted multivariable logistic regression analysis to estimate the odds ratios (ORs) for dyslipidemia, type 2 diabetes, the homeostasis model assessment of insulin resistance (HOMA-IR), and metabolic syndrome (MetS) according to sex-specific SFer quartiles (Q1 to Q4). Results revealed that the ORs for dyslipidemia increased progressively and significantly across the SFer quartiles, up to two folds in Q4 for women (OR 2.47 (1.68–3.62)) and men (OR 2.24 (1.41–3.55)) versus Q1 (OR:1). Exclusively in women, the ORs for IR (HOMA-IR > 3.58) increased significantly in Q4 (OR 1.79 (1.19–2.70)) versus OR 1 in Q1 as did the ORs for diabetes (OR: 2.03 (1.15–3.57) in Q4 versus OR 1 in Q1). We observed the same result when we pooled the participants with prediabetes and diabetes in one group. The OR for MetS also increased significantly across the Sfer Quartiles from OR: 1 in Q1 to 1.92 (1.06–3.02) in Q4 for women and to 2.07 (1.08–3.98) in Q4 in men. Our results suggest the elevated Sfer levels as a potential risk biomarker for dyslipidemia and MetS in adult Qatari men and women, and diabetes and IR in women only.
A family history of type 2 diabetes as a predictor of fatty liver disease in diabetes-free individuals with excessive body weight
Authors: De Pergola Giovanni , Castellana Fabio , Zupo Roberta , De Nucci Sara , Panza Francesco , Castellana Marco , Lampignano Luisa , Di Chito Martina , Triggiani Vincenzo , Sardone Rodolfo , Giannelli Gianluigi 
Published: December 2021

AbstractComprehensive screening for non-alcoholic fatty liver disease (NAFLD) may help prompt clinical management of fatty liver disease. A family history, especially of diabetes, has been little studied as a predictor for NAFLD. We characterized the cross-sectional relationship between a family history of type 2 diabetes (FHT2D) and NAFLD probability in 1185 diabetes-free Apulian (Southern-Italy) subjects aged > 20 years with overweight or obesity not receiving any drug or supplementation. Clinical data and routine biochemistry were analysed. NAFLD probability was defined using the fatty liver index (FLI). A first-degree FHT2D was assessed by interviewing subjects and assigning a score of 0, 1, or 2 if none, only one, or both parents were affected by type 2 diabetes mellitus (T2DM). Our study population featured most females (70.9%, N = 840), and 48.4% (N = 574) of the sample had first-degree FHT2D. After dividing the sample by a FHT2D, we found a higher BMI, Waist Circumference (WC), and diastolic blood pressure shared by FHT2D subjects; they also showed altered key markers of glucose homeostasis, higher triglyceride levels, and worse liver function. FLI scores were significantly lower in subjects without a first-degree FHT2D. After running logistic regression models, a FHT2D was significantly associated with the NAFLD probability, even adjusting for major confounders and stratifying by age (under and over 40 years of age). A FHT2D led to an almost twofold higher probability of NAFLD, regardless of confounding factors (OR 2.17, 95% CI 1.63 to 2.89). A first-degree FHT2D acts as an independent determinant of NAFLD in excess weight phenotypes, regardless of the age group (younger or older than 40 years). A NAFLD risk assessment within multidimensional screening might be useful in excess weight subjects reporting FHT2D even in the absence of diabetes.
Deep learning-based landslide susceptibility mapping
Authors: Azarafza Mohammad , Azarafza Mehdi , Akgün Haluk , Atkinson Peter M. , Derakhshani Reza 
Published: December 2021

AbstractLandslides are considered as one of the most devastating natural hazards in Iran, causing extensive damage and loss of life. Landslide susceptibility maps for landslide prone areas can be used to plan for and mitigate the consequences of catastrophic landsliding events. Here, we developed a deep convolutional neural network (CNN–DNN) for mapping landslide susceptibility, and evaluated it on the Isfahan province, Iran, which has not previously been assessed on such a scale. The proposed model was trained and validated using training (80%) and testing (20%) datasets, each containing relevant data on historical landslides, field records and remote sensing images, and a range of geomorphological, geological, environmental and human activity factors as covariates. The CNN–DNN model prediction accuracy was tested using a wide range of statistics from the confusion matrix and error indices from the receiver operating characteristic (ROC) curve. The CNN–DNN model was evaluated comprehensively by comparing it to several state-of-the-art benchmark machine learning techniques including the support vector machine (SVM), logistic regression (LR), Gaussian naïve Bayes (GNB), multilayer perceptron (MLP), Bernoulli Naïve Bayes (BNB) and decision tree (DT) classifiers. The CNN–DNN model for landslide susceptibility mapping was found to predict more accurately than the benchmark algorithms, with an AUC = 90.9%, IRs = 84.8%, MSE = 0.17, RMSE = 0.40, and MAPE = 0.42. The map provided by the CNN–DNN clearly revealed a high-susceptibility area in the west and southwest, related to the main Zagros trend in the province. These findings can be of great utility for landslide risk management and land use planning in the Isfahan province.
The production of biodiesel from plum waste oil using nano-structured catalyst loaded into supports
Authors: Saeed Aasma , Hanif Muhammad Asif , Nawaz Haq , Qadri Rashad Waseem Khan 
Published: December 2021

AbstractThe present study was undertaken with aims to produced catalyst loaded on low-cost clay supports and to utilize plum waste seed oil for the production of biodiesel. For this purpose, Bentonite–potassium ferricyanide, White pocha-potassium ferricyanide, Granite-potassium ferricyanide, Sindh clay-potassium ferricyanide, and Kolten-potassium ferricyanide composites were prepared. Transesterification of plum oil under the different conditions of reactions like catalysts concentrations (0.15, 0.3 and 0.6 g), temperature (50, 60, 70 and 80 °C), reaction time (2, 4 and 6 h) and oil to methanol ratio (1:10) was conducted. The maximum biodiesel yield was recorded for Bentonite–potassium ferricyanide composite. This composite was subjected to calcination process to produce Calcinized bentonite–potassium ferricyanide composite and a further improvement in biodiesel amount was recorded. The fuel quality parameters of all biodiesel samples were in standard range. Gas chromatographic mass spectrometric analysis confirmed the presence of oleic and linoleic acids in the plum seed oil. The characterization of composite was done using FTIR, SEM and EDX. Two infrared bands are observed in the spectrum from 1650 to 1630 cm−1 indicates that the composite materials contained highly hydrogen bonded water. The presence of surface hydroxyls groups can also be confirmed from FTIR data. SEM image clearly show the presence of nano-rods on the surface of Granite-potassium ferricyanide and Kolten-potassium ferricyanide composites. Another interesting observation that can be recorded from SEM images is the changes in surface characteristic of Bentonite–potassium ferricyanide composite after calcination (at 750 °C, 1 atm for 4 h). Calcinized bentonite–potassium ferricyanide composite found to contain more nano rod like structures at its surface as compared to Bentonite–potassium ferricyanide composite which contained spherical particles. EDX data of Bentonite–potassium ferricyanide composite and Calcinized bentonite–potassium ferricyanide composite show that after calcination carbon and oxygen was reduced. The other lost volatile compounds after calcination were of Na, Mg, Al, Si, and S. The XRD spectrum of pure bentonite showed the average crystal size of 24.46 nm and calcinized bentonite of 25.59 nm. The average crystal size of bentonite and potassium ferricyanide composite and its calcinized form was around 33.76 nm and 41.05 nm, respectively.