bluuebunny/crossref_metadata_2025_split huggingface dataset:
Robustness of Hilbert space-valued stochastic volatility models
Authors: Benth Fred Espen , Eyjolfsson Heidar 
Published: September 2024

AbstractIn this paper, we show that Hilbert space-valued stochastic models are robust with respect to perturbations, due to measurement or approximation errors, in the underlying volatility process. Within the class of stochastic-volatility-modulated Ornstein–Uhlenbeck processes, we quantify the error induced by the volatility in terms of perturbations in the parameters of the volatility process. We moreover study the robustness of the volatility process itself with respect to finite-dimensional approximations of the driving compound Poisson process and semigroup generator, respectively, when considering operator-valued Barndorff-Nielsen and Shephard stochastic volatility models. We also give results on square root approximations. In all cases, we provide explicit bounds for the induced error in terms of the approximation of the underlying parameter. We discuss some applications to robustness of prices of options on forwards and volatility.
Investigation of ComBat Harmonization on Radiomic and Deep Features from Multi-Center Abdominal MRI Data
Authors: Jia Wei , Li Hailong , Ali Redha , Shanbhogue Krishna P. , Masch William R. , Aslam Anum , Harris David T. , Reeder Scott B. , Dillman Jonathan R. , He Lili 
Published: September 2024

AbstractComBat harmonization has been developed to remove non-biological variations for data in multi-center research applying artificial intelligence (AI). We investigated the effectiveness of ComBat harmonization on radiomic and deep features extracted from large, multi-center abdominal MRI data. A retrospective study was conducted on T2-weighted (T2W) abdominal MRI data retrieved from individual patients with suspected or known chronic liver disease at three study sites. MRI data were acquired using systems from three manufacturers and two field strengths. Radiomic features and deep features were extracted using the PyRadiomics pipeline and a Swin Transformer. ComBat was used to harmonize radiomic and deep features across different manufacturers and field strengths. Student’s t-test, ANOVA test, and Cohen’s F score were applied to assess the difference in individual features before and after ComBat harmonization. Between two field strengths, 76.7%, 52.9%, and 26.7% of radiomic features, and 89.0%, 56.5%, and 0.1% of deep features from three manufacturers were significantly different. Among the three manufacturers, 90.1% and 75.0% of radiomic features and 89.3% and 84.1% of deep features from two field strengths were significantly different. After ComBat harmonization, there were no significant differences in radiomic and deep features among manufacturers or field strengths based on t-tests or ANOVA tests. Reduced Cohen’s F scores were consistently observed after ComBat harmonization. ComBat harmonization effectively harmonizes radiomic and deep features by removing the non-biological variations due to system manufacturers and/or field strengths in large multi-center clinical abdominal MRI datasets.
Automated ASPECTS Segmentation and Scoring Tool: a Method Tailored for a Colombian Telestroke Network
Authors: Ortiz Esteban , Rivera Juan , Granja Manuel , Agudelo Nelson , Hernández Hoyos Marcela , Salazar Antonio 
Published: September 2024

AbstractTo evaluate our two non-machine learning (non-ML)-based algorithmic approaches for detecting early ischemic infarcts on brain CT images of patients with acute ischemic stroke symptoms, tailored to our local population, to be incorporated in our telestroke software. One-hundred and thirteen acute stroke patients, excluding hemorrhagic, subacute, and chronic patients, with accessible brain CT images were divided into calibration and test sets. The gold standard was determined through consensus among three neuroradiologist. Four neuroradiologist independently reported Alberta Stroke Program Early CT Scores (ASPECTSs). ASPECTSs were also obtained using a commercial ML solution (CMLS), and our two methods, namely the Mean Hounsfield Unit (HU) relative difference (RELDIF) and the density distribution equivalence test (DDET), which used statistical analyze the of the HUs of each region and its contralateral side. Automated segmentation was perfect for cortical regions, while minimal adjustment was required for basal ganglia regions. For dichotomized-ASPECTSs (ASPECTS < 6) in the test set, the area under the receiver operating characteristic curve (AUC) was 0.85 for the DDET method, 0.84 for the RELDIF approach, 0.64 for the CMLS, and ranged from 0.71–0.89 for the neuroradiologist. The accuracy was 0.85 for the DDET method, 0.88 for the RELDIF approach, and was ranged from 0.83 − 0.96 for the neuroradiologist. Equivalence at a margin of 5% was documented among the DDET, RELDIF, and gold standard on mean ASPECTSs. Noninferiority tests of the AUC and accuracy of infarct detection revealed similarities between both DDET and RELDIF, and the CMLS, and with at least one neuroradiologist. The alignment of our methods with the evaluations of neuroradiologist and the CMLS indicates the potential of our methods to serve as supportive tools in clinical settings, facilitating prompt and accurate stroke diagnosis, especially in health care settings, such as Colombia, where neuroradiologist are limited.
Cranial and spinal computed tomography (CT) angiography with photon-counting detector CT: comparison with angiographic and operative findings
Authors: Higaki Fumiyo , Hiramatsu Masafumi , Yasuhara Takao , Sasada Susumu , Otani Yoshihiro , Haruma Jun , Inoue Tomohiro , Morimitsu Yusuke , Akagi Noriaki , Matsui Yusuke , Iguchi Toshihiro , Hiraki Takao 
Published: September 2024

Abstract
The clinical imaging features of photon-counting detector (PCD) computed tomography (CT) are mainly known as dose reduction, improvement of spatial resolution, and reduction of artifacts compared to energy-integrating detector CT (EID-CT). The utility of cranial and spinal PCD-CT and PCD-CT angiography (CTA) has been previously reported. CTA is a widely used technique for noninvasive evaluation. Cranial CTA is important in brain tumors, especially glioblastoma; it evaluates whether the tumor is highly vascularized prior to an operation and helps in the diagnosis and assessment of bleeding risk. Spinal CTA has an important role in the estimation of feeders and drainers prior to selective angiography in the cases of spinal epidural arteriovenous fistulas and spinal tumors, especially in hemangioblastoma. So far, EID-CTA is commonly performed in an adjunctive role prior to selective angiography; PCD-CTA with high spatial resolution can be an alternative to selective angiography. In the cases of cerebral aneurysms, flow diverters are important tools for the treatment of intracranial aneurysms, and postoperative evaluation with cone beam CT with angiography using diluted contrast media is performed to evaluate stent adhesion and in-stent thrombosis. If CTA can replace selective angiography, it will be less invasive for the patient. In this review, we present representative cases with PCD-CT. We also show how well the cranial and spinal PCD-CTA approaches the accuracy of angiographic and intraoperative findings.
Novel approach of thionyl chloride detection and disposal using a benzimidazole-based derivative: perspectives and proposals
Authors: Kabaňová N. , Tokárová Z. 
Published: September 2024

AbstractBenzimidazoles are important heterocyclic compounds that exhibit a wide range of pharmacological and biological properties. Among all, sensitivity to Lewis acids provide a possibility to act as a fluorescent detectors for senzing the cathions, radicals, highly reactive low-molecular species with hazardous effects to environment and human health. Herein, we present the design and synthesis of N-((1H-benzo[d]imidazol-2-yl)methyl)cinnamamide (I) for the detection of readily reactive thionyl chloride (SOCl2). Treatment of SOCl2 with a novel benzimidazole-based compound I is accompanied by immediate color change. Although the process is irreversible the change noticeable by eye is profitable for a simple and rapid protection against the SOCl2 exposure at amounts harmful for surroundings and body. In the context of environmental issue, the chemical reaction between the detector I and thionyl chloride is beneficial for the safe waste disposal. Thionyl chloride is recaptured in the structure of I throughout the reaction leading to a formation of stable compound II. Incorporation of residual traces of SOCl2 into the structure of organic-type detector I represents effective route to achieve non-reactive and non-damaging derivatives. Accordingly, the organic non-liquid waste is subsequently stored and disposed in a safe manner.
Monocular Pose and Shape Reconstruction of Vehicles in UAV imagery using a Multi-task CNN
Authors: El Amrani Abouelassad S. , Mehltretter M. , Rottensteiner F. 
Published: September 2024

AbstractEstimating the pose and shape of vehicles from aerial images is an important, yet challenging task. While there are many existing approaches that use stereo images from street-level perspectives to reconstruct objects in 3D, the majority of aerial configurations used for purposes like traffic surveillance are limited to monocular images. Addressing this challenge, a Convolutional Neural Network-based method is presented in this paper, which jointly performs detection, pose, type and 3D shape estimation for vehicles observed in monocular UAV imagery. For this purpose, a robust 3D object model is used following the concept of an Active Shape Model. In addition, different variants of loss functions for learning 3D shape estimation are presented, focusing on the height component, which is particularly challenging to estimate from monocular near-nadir images. We also introduce a UAV-based dataset to evaluate our model in addition to an augmented version of the publicly available Hessigheim benchmark dataset. Our method yields promising results in pose and shape estimation: utilising images with a ground sampling distance (GSD) of 3 cm, it achieves median errors of up to 4 cm in position and 3° in orientation. Additionally, it achieves root mean square (RMS) errors of $$\pm 6$$ cm in planimetry and $$\pm 18$$ cm in height for keypoints defining the car shape.
Applying Insights from China: A Typology for Subnational Comparative Politics
Authors: Zhu Hongshen , Rothschild Viola 
Published: September 2024

AbstractIn this study, we draw on theories of subnational analysis and comparison to introduce a novel framework for better understanding central-local dynamics in China. We argue that careful consideration along the dimensions of interests and information of national and subnational actors can allow us to predict how the central state evaluates local actors, variation in local implementation, and the potential for findings to be generalized to settings beyond China. We apply this 2$$\times$$
×
2 typology to several policy areas—social stability, social security, environmental governance, and economic development—to derive expectations about the behavior of central and local states, and identify when researchers can (and cannot) treat subnational units as independent observations. By identifying the underlying dynamics of central-local relations in different policy domains, this typology provides researchers with tools to construct a more precise analytical framework and helps scholars of Chinese politics conducting subnational analyses design research agendas better able to contribute to the larger comparative politics literature.
Quantifying Sahel Runoff Sensitivity to Climate Variability, Soil Moisture and Vegetation Changes Using Analytical Methods
Authors: Nkiaka Elias , Bryant Robert G. , Dembélé Moctar 
Published: September 2024

Abstract
Whilst substantial efforts have been deployed to understand the “Sahel hydrological paradox”, most of the studies focused on small experimental watersheds around the central and western Sahel. To our knowledge, there is no study on this issue covering all the watersheds located within the Sahelian belt. The absence of relevant studies may be attributed to a sparsity of in situ data leading to a dearth of knowledge on the Sahel hydrology. To fill this knowledge gap, the present study leverages analytical methods and freely available geospatial datasets to understand the effects of climatic factors, soil moisture and vegetation cover changes on surface runoff in 45 watersheds located within the Sahelian belt over two decades (2000–2021). Analyses show increasing trends in annual precipitation and potential evapotranspiration (PET) in more than 80% of the watersheds. Surface runoff, soil moisture (SM), and vegetation cover measured using the normalised difference vegetation index (NDVI) also show increasing trends in all the watersheds. Multivariable linear regression (MLR) analyses reveal that precipitation, PET, SM, and NDVI contribute about 62% of surface runoff variance. Further analyses using MLR, and the partial least squares regression (PLSR) show that precipitation and NDVI are the main factors influencing surface runoff in the Sahel. Elasticity coefficients reveal that a 10% increase in precipitation, SM and NDVI may lead to about 22%, 26% and 45% increase in surface runoff respectively. In contrast, a 10% increase in PET may lead to a 61% decline in surface runoff in the Sahel. This is the first hydrological study covering all the watersheds located within the Sahelian belt with results showing that surface runoff is influenced by climate, SM and NDVI to varying degrees. Given the unique hydrological characteristics of the Sahel, a better understanding of the different factors influencing surface runoff may be crucial for enhancing climate adaptation and ecological restoration efforts in the region such as the Great Green Wall Initiative.
Lowering Barriers to Entry in Undergraduate Research Through Student-Led Virtual Workshops
Authors: Amelung Connor , Helmke Brian P. 
Published: September 2024

Abstract
Undergraduate research is a high-impact learning experience, but undergraduate students interested in research often face high barriers to entry, such as limited guidance, confusing application processes, and feelings of not belonging. These barriers are especially prohibitive to first-year students, first-generation students, and members of underrepresented groups, and COVID-19 exacerbated the difficulty of undergraduates joining research by reducing opportunities to gain meaningful research experiences. To address these challenges, we designed a novel extracurricular education program named Starting an Undergraduate Research Experience (SURE) in the fall 2020 with the goal of lowering barriers to entry for engineering students to gain research experiences. Over 150 students enrolled in the workshop series throughout both semesters and were put into small groups led by research-experienced undergraduate peer mentors to cement skills from the workshop and to answer students’ questions on a one-on-one basis. A pre- and post-workshop survey was administered to measure students’ major interests, how they define research and engineering, sense of belonging, and perceived barriers to getting involved in research. After participating in SURE, students reported lower perceived barriers to entry in research and were more likely to obtain a research position.
Comparison of Commercial Collagen and Marine Collagen: Efficiency and Effects on the Formation of EDC/NHS-Crosslinked Membranes
Authors: Núñez-Tapia Israel Alfonso , Vázquez-Vázquez Febe Carolina , Mendoza Olga Flores , Bucio-Galindo Lauro , Álvarez-Pérez Marco Antonio , Barba María Cristina Piña 
Published: September 2024

AbstractThis study investigates the extraction and characterisation of collagen derived from fish skin and scales, the collagens obtained were used to produce membranes which were subsequently cross-linked by EDC/NHS. A comprehensive investigation of their microstructure, composition, mechanical properties, swelling, degradation, thermal properties and a 24 h cell viability test was carried out. The results showed that the yields of collagen from skin and fish scales were 25.14 ± 2.90 and 29.26 ± 2.53%, respectively. Mechanical stress tests showed that membranes made from fish skin collagen and commercial collagen had comparable load-bearing capacities before failure. The Young’s modulus of the membranes was 9.45 MPa ± 1.77 for commercial collagen, 5.76 MPa ± 0.74 for fish skin collagen and 2.43 MPa ± 0.78 for fish scale collagen, this similarity was maintained in degradation tests and at denaturation temperature (75 °C).These results demonstrate the viability of collagen derived from marine by-products as an effective and efficient alternative for biomedical and tissue engineering applications.
Greenhouse gas emissions from Chinese livestock sector can be decreased by one third in 2030 by the improvement in management
Authors: Chen Yulong , Qi Le , Hussain Hafiz Athar 
Published: September 2024

AbstractChina is one of the largest contributors to global greenhouse gas (GHG) emissions, and the livestock sector is a major source of non-CO2 GHG emissions. Mitigation of GHG emissions from the livestock sector is beneficial to the sustainable development of the livestock sector in China. This study investigated the provincial level of GHG emissions from the livestock sector between 2000 and 2020 in China, to determine the driving factors affecting the provincial-level GHG emissions from the livestock sector, based on the logarithmic mean Divisia index (LMDI) model, which took into account of technological progress, livestock structure, economic factor, and agricultural population. Moreover, a gray model GM (1, 1) was used to predict livestock GHG emissions in each province until 2030 in China. The results showed that the GHG of Chinese livestock sector was decreased from 195.1 million tons (MT) CO2e in 2000 to 157.2 MT CO2e in 2020. Henan, Shandong, and Hebei provinces were the main contributors to the reduction in Chinese livestock GHG emissions, with their livestock GHG emissions reduced by 60.1%, 53.5% and 45.5%, respectively, in 2020 as compared to 2000. The reduction in GHG emissions from the Chinese livestock sector can be attributed to two main factors: technological progress and the shrinking of the agricultural laborers. In contrast, the agricultural economic development model with high input and high emissions showed a negative impact on GHG emission reduction in China’s livestock sector. Furthermore, the different livestock structure in each province led to different GHG reduction effects on the livestock sector. Under the gray model GM (1,1), the GHG emissions of the livestock sector will be reduced by 33.7% in 2030 as compared with 2020 in China, and the efficiency factor will account for 76.6% of the positive effect of GHG reduction in 2030. The eastern coastal region will be the main contributor to the reduction of GHG emissions from the Chinese livestock sector in 2030. Moreover, recommendations (such as upgrading livestock management methods and promoting carbon emission mitigation industries) should be proposed for the environmentally sustainable development of the livestock sector in the future.
Mentoring up: How mentorship training influences mentee intent to change behavior
Authors: Orsini Jonathan , Hyun So Hee , Sancheznieto Fatima 
Published: September 2024

Abstract

Introduction:
The purpose of this study was to evaluate data from different implementations of the Mentoring Up curriculum, designed by the Center for the Improvement of Mentored Experiences in Research. The study investigated the relationship between participants’ self-reported change in mentoring competence and the behaviors they intended to implement post-training.

Methods:
The data set included 401 respondents who consented to participate after 59 Mentoring Up training events hosted by 34 institutions between 2015 and 2022. Responses to the Mentoring Competency Assessment (MCA) were analyzed to determine which factors were related to self-reported changes in participants’ mentoring competencies post-training.

Results:
Quantitative analysis showed that intent to change, perceived value of training, training modality, and prior mentor training were all significantly associated with the magnitude of change in MCA scores between pre- and post-tests. Further, participants who engaged in face-to-face training found significantly more value in the training than those who participated online. Analysis of open-ended questions demonstrated that participants with larger changes in MCA scores were more likely to address core principles of Mentoring Up curriculum when discussing their behavior change plans post-training.

Conclusion:
Participants improved their mentoring competence by participating in the Mentoring Up curriculum, and this change was significantly and practically associated with an intent to modify their behavior in their mentoring relationships.
Supporting students from underrepresented minority backgrounds in graduate school: A mixed-methods formative study to inform post-baccalaureate design
Authors: Sperling Jessica B. , Roth Noelle E. Wyman , Welsh Whitney E. , McElvaine Allison T. , Permar Sallie R. , Gbadegesin Rasheed A. 
Published: September 2024

Abstract
The US biomedical research workforce suffers from systemic barriers causing insufficient diversity and perpetuating inequity. To inform programming enhancing graduate program access, we implemented a formative mixed-method study to identify needed supports for program applications and graduate program success. Overall, results indicate value in added supports for understanding application needs, network development, critical thinking, time management, and reading academic/scientific literature. We find selected differences for underrepresented minority (URM) students compared to others, including in the value of psychosocial supports. This work can inform broader efforts to enhance graduate school access and provides foundation for further understanding of URM students’ experiences.
Just Research: Evaluation findings of an educational program to promote inclusive research among investigators and research staff
Authors: Passmore Susan Racine , Green-Harris Gina , Kirschmann Peter , Filut Amarette , Phelps Katrina , Garcia Mariana , Farrar Edwards Dorothy 
Published: September 2024

Abstract
Educational opportunities for investigators and staff to promote inclusive research practices are a critical piece of the effort to increase diversity in study participation and promote health equity. However, few trainings to date have empirically been shown to result in behavior changes. We present preliminary evaluation findings for the Just Research workshop offered at the University of Wisconsin–Madison between October 2022 and August 2023. These sessions included 80 participants who made up 4 cohorts. Data was collected through a retrospective pre/post-test survey administered 0–7 days following the workshop (n = 70), and a follow-up survey administered 9–12 months following the workshop (n = 21). Participants demonstrate significant increases in knowledge and self-efficacy regarding implementing inclusive practices post-intervention (p < .001). 85.7% of participants who completed the follow-up survey reported implementing inclusive practices.