bluuebunny/crossref_metadata_2025_split huggingface dataset:
Different characteristics of two surges in Weigeledangxiong Glacier, northeastern Tibetan Plateau
Authors: Pan Baotian , Guan Weijin , Shi Menghan , Wu Guangjian , Cheng Jiamei , Shangguan Donghui , Guo Wanqin , Cao Bo 
Published: October 2022

Abstract
Glacier surge is a special form of glacier displacement caused by the instability of the glacial dynamic system. It is a quasi-periodic oscillation behavior, which affects the estimation of the overall change of glaciers in the region and potentially threatens the infrastructure and human life in the downstream regions. Most glaciers experience a mass loss with rising air temperatures in recent decades, but little attention has been paid to the influence of climate change on glacial surges. This study identified two surges, triggered in 1992 and 2015 in Weigeledangxiong Glacier, Ányêmaqên Mountains, northeastern Tibetan Plateau, using multi-source remote sensing data (Landsat images, Sentinel-2 images, topographic map, shuttle radar topography mission digital elevation model [SRTM DEM], and the elevation change database). The 1992 surge accelerated abruptly with the maximum velocity of 350 ± 9 m a−1, and a large volume of ice transported downward, causing a sudden advance of 392 ± 42 m from 1992 to 1994, and clear thickening of the ice tongue. The recent surge is still in the active phase, exhibiting a gentler process of slower advance speed and lower peak velocity, as well as a smaller expansion zone than the previous one. These phenomena may be associated with the reduced glacier basal resistance and energy caused by rising temperatures in recent decades. Higher temperatures may cause the discharge of subglacial water through a more developed drainage system, leading to a longer active phase duration. Similar phenomena may exist widely in the Tibetan Plateau and its surrounding areas. Meanwhile, the frontal position of Weigeledangxiong Glacier advancing in the recent surge is not expected to threaten roads near the ice tongue.
Augmenting agroecosystem models with remote sensing data and machine learning increases overall estimates of nitrate-nitrogen leaching
Authors: Nowatzke Matthew , Damiano Luis , Miguez Fernando E , McNunn Gabe S , Niemi Jarad , Schulte Lisa A , Heaton Emily A , VanLoocke Andy 
Published: October 2022

Abstract
Process-based agroecosystem models are powerful tools to assess performance of managed landscapes, but their ability to accurately represent reality is limited by the types of input data they can use. Ensuring these models can represent cropping field heterogeneity and environmental impact is important, especially given the growing interest in using agroecosystem models to quantify ecosystem services from best management practices and land use change. We posited that augmenting process-based agroecosystem models with additional field-specific information such as topography, hydrologic processes, or independent indicators of yield could help limit simulation artifacts that obscure mechanisms driving observed variations. To test this, we augmented the agroecosystem model Agricultural Production Systems Simulator (APSIM) with field-specific topography and satellite imagery in a simulation framework we call Foresite. We used Foresite to optimize APSIM yield predictions to match those created from a machine learning model built on remotely sensed indicators of hydrology and plant productivity. Using these improved subfield yield predictions to guide APSIM optimization, total

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loss estimates increased by 39% in maize and 20% in soybeans when summed across all years. In addition, we found a disproportionate total amount of leaching in the lowest yielding field areas vs the highest yielding areas in maize (42% vs 15%) and a similar effect in soybeans (31% vs 20%). Overall, we found that augmenting process-based models with now-common subfield remotely sensed data significantly increased values of predicted nutrient loss from fields, indicating opportunities to improve field-scale agroecosystem simulations, particularly if used to calculate nutrient credits in ecosystem service markets.
Nighttime light data reveal lack of full recovery after hurricanes in Southern US
Authors: Barton-Henry Kelsey , Wenz Leonie 
Published: October 2022

Abstract
As the climate warms, many areas of the world are experiencing more frequent and extreme weather events. Hurricanes carry some of the costliest short-term socioeconomic repercussions via economic losses and people displaced. There is, however, little quantitative evidence regarding medium- to long-term effects, nor factors moderating recovery. Here we show that areas affected by hurricanes of category 4 or 5 in the southern US between 2014 and 2020 generally do not demonstrate full recovery in the longer term. Utilizing Visible Infrared Imaging Radiometer Suite nighttime light (NTL) data as a proxy for economic activity and population density, we build a timeline of recovery via NTL radiance levels. We exploit the difference in the eligibility for aid from the Federal Emergency Management Agency (FEMA) to apply a quasi-experimental method to identify changes in NTL radiance attributable to hurricanes. We find that after three years, affected areas demonstrate a reduction in NTL radiance levels of between 2% and 14% compared to the pre-disaster period. Combining these results with machine learning techniques, we are able to investigate those factors that contribute to recovery. We find counties demonstrating smaller reductions in NTL radiance levels in the months following the hurricane are buoyed by the amount of FEMA aid received, but that this aid does not foster a longer-term return to normal radiance levels. Investigating areas receiving FEMA aid at the household and individual level, we find age and employment are more important than other demographic factors in determining hurricane recovery over time. These findings suggest that aid may be more important in motivating short-term recovery for public entities than for individuals but is not sufficient to guarantee complete recovery in the longer term.
All noncommutative spaces of κ-Poincaré geodesics
Authors: Ballesteros Angel , Gutierrez-Sagredo Ivan , Herranz Francisco J 
Published: October 2022

Abstract
Noncommutative spaces of geodesics provide an alternative way of introducing noncommutative relativistic kinematics endowed with quantum group symmetry. In this paper we present explicitly the seven noncommutative spaces of time-, space- and light-like geodesics that can be constructed from the time-, space- and light-versions of the κ-Poincaré quantum symmetry in (3 + 1) dimensions. Remarkably enough, only for the light-like (or null-plane) κ-Poincaré deformation the three types of noncommutative spaces of geodesics can be constructed, while for the time-like and space-like deformations both the quantum time-like and space-like geodesics can be defined, but not the light-like one. This obstruction comes from the constraint imposed by the coisotropy condition for the corresponding deformation with respect to the isotropy subalgebra associated to the given space of geodesics, since all these quantum spaces are constructed as quantizations of the corresponding classical coisotropic Poisson homogeneous spaces. The known quantum space of geodesics on the light cone is given by a five-dimensional homogeneous quadratic algebra, and the six nocommutative spaces of time-like and space-like geodesics are explicitly obtained as six-dimensional nonlinear algebras. Five out of these six spaces are here presented for the first time, and Darboux generators for all of them are found, thus showing that the quantum deformation parameter κ
−1 plays exactly the same algebraic role on quantum geodesics as the Planck constant ℏ plays in the usual phase space description of quantum mechanics.
Production of an electrolyte drink from the use of tamarind fruit (Tamarindus indica L.)
Authors: Vidal-Tovar C.R. , Gordon-Hernández Y. , Fragoso-Castilla P. J. , Gutierrez De Piñeres C.A. , Angulo-Blanquicett G. E. 
Published: October 2022

Abstract
The tamarind (Tamarindus indica L.), is from the legume family and is native to the tropics. The fruit is curved, which the shell is bright brown and its flattened oval seeds, joined together by fibers. It is a highly rustic fruit tree, since it can thrive in poor or marginalized soils, with little or no irrigation and minimal care, in relation to other tropical fruit trees. The objective of this work was to establish the formulation process to obtain a hydrating drink based on Tamarindus indica L., To obtain the drink, the following formulations were made; formulation 1 (6% tamarind pulp - 94% H2O), formulation 2 (9% tamarind pulp - 91% H2O) and formulation 3 (12% tamarind pulp - 88% H2O), keeping the amounts of electrolytes and carbohydrates constant added to the formulation. As the main result for the formulation of the drink, there is the following sequence: Harvesting of the fruit, Selection and classification of the raw material, Pulping, Storage of the pulp, Formulation, Mixing, Pasteurization, Packaging and Storage.
Probabilistic Seismic Hazard Analysis of San José de Cúcuta, Colombia
Authors: Flórez-Góngora C H , Sereno-Vargas B S , Lozano-Lozano C F 
Published: October 2022

Abstract
This work evaluated the probabilistic seismic hazard of San José de Cúcuta (Colombia) using the methodology developed by Hanks and Cornell. Seismic hazard curves were obtained using a set of ground movement prediction equation which relate the average annual rate of earthquake exceedance against maximum acceleration values, assuming that the occurrence of the events presented in the area within the time period analyzed follows a Poisson´s distribution. Additionally, the average maximum acceleration values were calculated for a set of return periods, which were compared against the effective peak ground acceleration value for the city established in the current anti-seismic design code in Colombia. For the return period of 475 years, maximum acceleration values greater than those defined in the regulation were obtained with two of the soil movement prediction equations. With the results obtained, the level of high seismic threat in which the city is located has been corroborated and it is proposed to increase the maximum horizontal acceleration for anti-seismic design code from 0.35g to 0.40g.
Machine Learning algorithms to predict desertion in the faculty of Engineering Sciences at the Corporación Universitaria Antonio José de Sucre.
Authors: Pineda-Pertuz C M , Martinez Y. , Diaz I. 
Published: October 2022

Abstract
Desertion can be understood as the withdrawal and subsequent abandonment of school activity by students, due to different family, economic, social and other factors. All educational levels are affected by this scourge, being the university one of the most affected, especially during this time of pandemic caused by the SARS-CoV 19 virus. Due to the complexity of this problem, and the great impact it has generated at the educational level, many universities have proposed different intervention strategies to reduce dropout rates. The difficulty is that many of these strategies lack effectiveness, since they do not take into account the different causes, which are different for each case. On the other hand, it is important to have accurate and reliable information to determine the population in order to identify possible cases of dropout, and to take preventive actions to reduce the student dropout rate. In this sense, the purpose of this study is to analyze different predictive algorithms based on Machine Learning that enable early detection of possible cases of desertion in the Faculty of Engineering at the Corporación Universitaria Antonio José De Sucre. Among such algorithms we can mention decision trees, logistic regression and support vector machines. These will be trained with historical data and then tested to determine their performance, to finally choose the most appropriate within the context of the current problem.
Research methodology to pineapple fiber reinforcement effect in polylactic material
Authors: Cárdenas-Arias C G , Zuza-Hernández E , Quiroga-Méndez J E , Sandoval-Rodriguez C L , Rincón-Quintero A D , Castillo-León N Y 
Published: October 2022

Abstract
Researching new materials that are environment friendly has become a global purpose. Given the current contamination situation, mainly due to plastic, the using pineapple waste option as a bio composite production source is presented. The methodology used in this project is presented to achieve the material’s development, the problems presented and the results obtained in the work progress.
Study on rheological properties of warm mix large proportion recycled asphalt
Authors: Li Zhenxia , Guo Tengteng , Chen Yuanzhao , Bian Xuewei , Jiang Xiaoxiao , Hao Menghui , Zhao Xu , Liu Jinyuan 
Published: October 2022

Abstract
In order to explore the rheological properties of high content warm mix recycled asphalt binder, recycled asphalt was added into warm mix asphalt to prepare warm mix recycled asphalt. The optimum content of regenerant and Sasobit REDUX was determined by asphalt basic performance test and temperature scanning test. The chemical composition of recycled asphalt was studied by FITR. The rheological properties and low temperature crack resistance of warm mix recycled asphalt were analyzed by DSR and BBR tests, and the optimum content of recycled asphalt was determined. The results show that when the content of regenerant is 10%, its basic performance recovers to the level of base asphalt. Sasobit REDUX can reduce the high temperature viscosity of asphalt, and the optimum content is 1%. With the increase of recycled asphalt content, the shear modulus and phase angle of warm mix recycled asphalt gradually decrease, and its high temperature stability gradually increases. Under low frequency and high temperature conditions, warm mix recycled asphalt with 50% content has better high temperature deformation resistance. Under the action of stress, the strain accumulation decreases with the increase of the content of recycled asphalt. When the content of recycled asphalt is 50%, the ability of warm mix recycled asphalt to resist load deformation and temperature sensitivity in the middle temperature zone is similar to that of matrix asphalt, and it has good deformation resistance and low temperature crack resistance. Comprehensive analysis of the best content of recycled asphalt should be 50%, then warm mix recycled asphalt mixture has excellent road performance.
Ferroelectric-like behavior in HfO2/Al2O3/AlN metal-insulator-semiconductor capacitor through AlN thermal stress
Authors: Kao Min-Lu , Lin Yuan , Weng You-Chen , Dee Chang-Fu , Chang Edward Yi 
Published: October 2022

Abstract
By modulating the thermal stress during film growth, the strained aluminum nitride (AlN) thin films with ferroelectric-like behavior were successfully grown by metal organic chemical vapor phase deposition (MOCVD) on silicon (Si) (111) substrate. The capacitors with strained AlN were fabricated and experimentally demonstrated, the linear to ferroelectric-like behavior on the fabricated AlN capacitors was observed, and the behavior was explained in terms of residual strains in the film. This work reports the ferroelectric-like properties of AlN film grown under specific deposition conditions for the first time.
Virtual and real-world implementation of deep-learning-based image denoising model on projection domain in digital tomosynthesis and cone-beam computed tomography data
Authors: Jin David Shih-Chun , Chang Li-Sheng , Wang Yu-Hong , Chen Jyh-Cheng , Tseng Snow H , Liu Tse-Ying 
Published: October 2022

Abstract
Reducing the radiation dose will cause severe image noise and artifacts, and degradation of image quality will also affect the accuracy of diagnosis. To find a solution, we comprise a 2D and 3D concatenating convolutional encoder-decoder (CCE-3D) and the structural sensitive loss (SSL), via transfer learning (TL) denoising in the projection domain for low-dose computed tomography (LDCT), radiography, and tomosynthesis. The simulation and real-world practicing results show that many of the figures-of-merit (FOMs) increase in both projections (2–3 times) and CT imaging (1.5–2 times). From the PSNR and structural similarity index of measurement (SSIM), the CCE-3D model is effective in denoising but keeps the shape of the structure. Hence, we have developed a denoising model that can be served as a promising tool to be implemented in the next generation of x-ray radiography, tomosynthesis, and LDCT systems.
Use of 2-Stage Modeling to Identify How Colorectal Cancer Risk Changes With Period and Cohort
Authors: DeYoreo Maria , Rutter Carolyn M , Lee Sarita D 
Published: October 2022

Abstract
Colorectal cancer (CRC) incidence rates have decreased among adults aged 50 years or older while increasing in adults under age 50 years. Understanding these trends is challenging because of the multiple related time scales of age, diagnosis period, and birth cohort. We analyzed incidence rates of rectal, distal colon, and proximal colon cancer for individuals aged 20 years or more from the Surveillance, Epidemiology, and End Results Program for diagnosis years 1978–2017. We used a 2-stage generalized linear model to determine age, period, and cohort effects for CRC incidence. We first estimated birth cohort effects among people under age 45 years. We used these results to specify prior distributions for cohort effects in a Bayesian model to estimate period effects among people aged 45 years or more. There was no evidence of period effects for people under age 45 years. Risks of rectal and distal colon cancer increased for later birth cohorts. Compared with the 1943–1952 birth cohort, the 1983–1992 birth cohort had 2.2 times the risk of rectal cancer, 1.9 times the risk of distal colon cancer, and 1.3 times the risk of proximal colon cancer. For people aged ≥45 years, period effects showed declines in CRC risk that were attributable to screening.
β-sitosterol from Clinacanthus nutans Lindau enhances osteoblastogenic activity via upregulation of differentiation related genes and proteins
Authors: Nguyen Huyen T T , Ngo Quang V , Le Duong T T , Nguyen Minh T H , Nguyen Phuong T M 
Published: October 2022

ABSTRACT
β-sitosterol derived from Clinacanthus nutans Lindau was tested for its in vitro osteogenic activity using MC3T3-E1 pre-osteoblasts. Our results indicated that β-sitosterol was non-toxic to the cells cultured at a concentration &lt;20 µg/mL. Treatment of the cells with β-sitosterol significantly enhanced the alkaline phosphatase activity up to 210 and 204.6% at 5 and 10 µg/mL, respectively (P &lt; .05). Similarly, the mineralization activity of the β-sitosterol treated cells was elevated up to 134, 168, 118% at a concentration of 2.5, 5, and 10 µg/mL, respectively (P &lt; .05). In addition, this compound up-regulated several marker genes for osteoblast differentiation, including runx2, osx and col I to 2, 2.5 and 5.6 folds at 10 µg/mL, respectively (P &lt; .05). The expression of p38 and ERK proteins involved in the MAPK signal pathway related to mineralization and differentiation was also enhanced. Thus, the osteoblastogenic activity of β-sitosterol was fully illustrated for the first time.
The Productivity Puzzle in Invasion Science: Declining but Persisting Gender Imbalances in Research Performance
Authors: Campbell Sara E , Simberloff Daniel 
Published: October 2022

Abstract
We analyzed 27,234 publications published since the rise of the field of invasion science in 1980 to evaluate the presence of gender differences in research productivity, the extent of collaboration, and the research impact of those differences. Our analysis revealed significantly fewer female than male authored publications, both per capita and as a group, and the underrepresentation of women as first and single authors persists despite improvements in the gender gap. At the current rate of increase, gender parity in first authorship will not be achieved until 2100, and men will continue to constitute the principal voice of first or single authors in invasion science. Women collaborate with fewer coauthors and are cited less frequently than men, on average, which may influence recruitment and retention to more senior academic positions. These gender disparities in this aspect of research performance suggest that, although the gender gap is lessening, women experience barriers in invasion science.
Investigational Study of DASATINIB N-Oxide Impurity in Different Diluents
Authors: Prasad Ketha Naga Venkata Durga , Kolli Deepti 
Published: October 2022

Abstract
Dasatinib is an aminopyrimidine used as an inhibitor of multiple tyrosine kinases in two different formulations an immediate-release tablet and a powder for oral suspension. It shows a very low pH-dependent solubility in aqueous solutions and higher solubility in organic solvents. The solubility plays an essential role in analytical methodology to establish the purity, potency, safety and efficacy of any drug product as a diluent. Also, extraction of active drug substance with a suitable diluent from matrix composition is crucial for any analytical method development. However, a diluent optimization study during the method development of related substances for the drug product reveals that the Piperazine ring presented in Dasatinib is susceptible to oxidation and forms an N-oxide impurity. The impurity formation is due to the micro oxidic properties of the solvent used as a diluent which is inducing an oxidation reaction. Therefore, a comprehensive investigative study was conducted to optimize the diluent by limiting N-Oxide generation.