bluuebunny/crossref_metadata_2025_split huggingface dataset:
Time Adaptivity in Model Predictive Control
Authors: Alla Alessandro , Gräßle Carmen , Hinze Michael 
Published: November 2021

AbstractThe core of the Model Predictive Control (MPC) method in every step of the algorithm consists in solving a time-dependent optimization problem on the prediction horizon of the MPC algorithm, and then to apply a portion of the optimal control over the application horizon to obtain the new state. To solve this problem efficiently, we propose a time-adaptive residual based a-posteriori error control concept based on the optimality system of this optimal control problem. This approach not only delivers an adaptive time discretization of the prediction horizon, but also suggests an adaptive time discretization of the application horizon, whose length could be either adaptive or fixed. We apply this concept for systems governed by linear parabolic PDEs and present several numerical examples which demonstrate the performance and the robustness of our adaptive MPC control concept.
Automated extraction of revision events from keystroke data
Authors: Conijn Rianne , Dux Speltz Emily , Chukharev-Hudilainen Evgeny 
Published: November 2021

AbstractRevision plays an important role in writing, and as revisions break down the linearity of the writing process, they are crucial in describing writing process dynamics. Keystroke logging and analysis have been used to identify revisions made during writing. Previous approaches include the manual annotation of revisions, building nonlinear S-notations, and the automated extraction of backspace keypresses. However, these approaches are time-intensive, vulnerable to construct, or restricted. Therefore, this article presents a computational approach to the automatic extraction of full revision events from keystroke logs, including both insertions and deletions, as well as the characters typed to replace the deleted text. Within this approach, revision candidates are first automatically extracted, which allows for a simplified manual annotation of revision events. Second, machine learning is used to automatically detect revision events. For this, 7120 revision events were manually annotated in a dataset of keystrokes obtained from 65 students conducting a writing task. The results showed that revision events could be automatically predicted with a relatively high accuracy. In addition, a case study proved that this approach could be easily applied to a new dataset. To conclude, computational approaches can be beneficial in providing automated insights into revisions in writing.
High frequency un-mixing of soil samples using a submerged spectrophotometer in a laboratory setting—implications for sediment fingerprinting
Authors: Lake Niels F. , Martínez-Carreras Núria , Shaw Peter J. , Collins Adrian L. 
Published: November 2021

Abstract
Purpose
This study tests the feasibility of using a submersible spectrophotometer as a novel method to trace and apportion suspended sediment sources in situ and at high temporal frequency.

Methods
Laboratory experiments were designed to identify how absorbance at different wavelengths can be used to un-mix artificial mixtures of soil samples (i.e. sediment sources). The experiment consists of a tank containing 40 L of water, to which the soil samples and soil mixtures of known proportions were added in suspension. Absorbance measurements made using the submersible spectrophotometer were used to elucidate: (i) the effects of concentrations on absorbance, (ii) the relationship between absorbance and particle size and (iii) the linear additivity of absorbance as a prerequisite for un-mixing.

Results
The observed relationships between soil sample concentrations and absorbance in the ultraviolet visible (UV–VIS) wavelength range (200–730 nm) indicated that differences in absorbance patterns are caused by soil-specific properties and particle size. Absorbance was found to be linearly additive and could be used to predict the known soil sample proportions in mixtures using the MixSIAR Bayesian tracer mixing model. Model results indicate that dominant contributions to mixtures containing two and three soil samples could be predicted well, whilst accuracy for four-soil sample mixtures was lower (with respective mean absolute errors of 15.4%, 12.9% and 17.0%).

Conclusion
The results demonstrate the potential for using in situ submersible spectrophotometer sensors to trace suspended sediment sources at high temporal frequency.
Utilization of Maternal Health Care Among Immigrant Mothers in New York City, 2016–2018
Authors: Maru Sheela , Glenn Lily , Belfon Kizzi , Birnie Lauren , Brahmbhatt Diksha , Hadler Max , Janevic Teresa , Reynolds Simone 
Published: November 2021

AbstractImmigrant women represent half of New York City (NYC) births, and some immigrant groups have elevated risk for poor maternal health outcomes. Disparities in health care utilization across the maternity care spectrum may contribute to differential maternal health outcomes. Data on immigrant maternal health utilization are under-explored in the literature. We conducted a cross-sectional analysis of the population-based NYC Pregnancy Risk Assessment Monitoring System survey, using 2016–2018 data linked to birth certificate variables, to explore self-reported utilization of preconception, prenatal, and postpartum health care and potential explanatory pathways. We stratified results by maternal nativity and, for immigrants, by years living in the US; geographic region of origin; and country of origin income grouping. Among immigrant women, 43% did not visit a health care provider in the year before pregnancy, compared to 27% of US-born women (risk difference [RD] = 0.16, 95% CI [0.13, 0.20]), 64% had no dental cleaning during pregnancy compared to 49% of US-born women (RD = 0.15, 95% CI [0.11, 0.18]), and 11% lost health insurance postpartum compared to 1% of US-born women (RD = 0.10, 95% CI [0.08, 0.11]). The largest disparities were among recent arrivals to the US and immigrants from countries in Central America, South America, South Asia, and sub-Saharan Africa. Utilization differences were partially explained by insurance type, paternal nativity, maternal education, and race and ethnicity. Disparities may be reduced by collaborating with community-based organizations in immigrant communities on strategies to improve utilization and by expanding health care access and eligibility for public health insurance coverage before and after pregnancy.
Effect of Alloying Additions on Microstructure, Mechanical and Magnetic Properties of Rapidly Cooled Bulk Fe-B-M-Cu (M = Ti, Mo and Mn) Alloys
Authors: Hasiak Mariusz , Tkaczyk Marzena , Łaszcz Amadeusz , Olszewski Jacek 
Published: November 2021

Abstract
The influence of alloying additions on the microstructure, mechanical, and magnetic properties of bulk Fe79B20Cu1, Fe79B16Ti4Cu1, Fe79B16Mo4Cu1 and Fe79B16Mn4Cu1 (at. pct) alloys was investigated. Nanocrystalline samples in the form of 3 mm rods were prepared directly by suction casting without additional heat treatment. Mössbauer spectroscopy, transmission electron microscopy and scanning electron microscopy studies confirmed that the investigated alloys consist α-Fe and Fe2B nanograins embedded in an amorphous matrix. The addition of alloying elements, such as Ti, Mo and Mn to Fe79B20Cu1 alloy increases the amount of amorphous phase and decreases the presence of Fe2B phase in all examined alloys. The mechanical properties of the samples, such as hardness, elastic modulus, and elastic energy ratio, were analysed by an instrumented indentation technique performed on a 12 × 12 nanoindentation grid. These tests allowed to characterise the mechanical properties of the regions observed in the same material. For the Fe79B20Cu1 alloy, the hardness of 1508 and 1999 HV, as well as Young’s modulus of 287 and 308 GPa, were estimated for the amorphous- and nanocrystalline-rich phase, respectively. The addition of Ti, Mo, and Mn atoms leads to a decrease in both hardness and elastic modulus for all regions in the investigated samples. Investigations of thermomagnetic characteristics show the soft magnetic properties of the studied materials. More detailed studies of magnetisation versus magnetic field curves for the Fe79B20−x
M
x
Cu1 (where x = 0 or 4; M = Ti, Mo, Mn) alloy, recorded in a wide range of temperatures, followed by the law of approach to magnetic saturation revealed the relationship between microstructure and magneto-mechanical properties.
Astrocytes in depression and Alzheimer’s disease
Authors: Liao Yang , Xing Qu , Li Qianqian , Zhang Jing , Pan Ruiyuan , Yuan Zengqiang 
Published: November 2021

AbstractAstrocytes are an abundant subgroup of cells in the central nervous system (CNS) that play a critical role in controlling neuronal circuits involved in emotion, learning, and memory. In clinical cases, multiple chronic brain diseases may cause psychosocial and cognitive impairment, such as depression and Alzheimer’s disease (AD). For years, complex pathological conditions driven by depression and AD have been widely perceived to contribute to a high risk of disability, resulting in gradual loss of self-care ability, lower life qualities, and vast burden on human society. Interestingly, correlational research on depression and AD has shown that depression might be a prodrome of progressive degenerative neurological disease. As a kind of multifunctional glial cell in the CNS, astrocytes maintain physiological function via supporting neuronal cells, modulating pathologic niche, and regulating energy metabolism. Mounting evidence has shown that astrocytic dysfunction is involved in the progression of depression and AD. We herein review the current findings on the roles and mechanisms of astrocytes in the development of depression and AD, with an implication of potential therapeutic avenue for these diseases by targeting astrocytes.
Activation of Three Major Signaling Pathways After Endurance Training and Spinal Cord Injury
Authors: Kiss Bimbova Katarina , Bacova Maria , Kisucka Alexandra , Galik Jan , Zavacky Peter , Lukacova Nadezda 
Published: November 2021

AbstractWe aimed to investigate the effects of endurance training on expression of growth factors (GFs) and stimulation of neurotrophin-dependent signaling pathways (PI3k/Akt, PLCγ/PKC, PLCγ/CAMKII, Ras-Erk1/2 and Rac1-Cdc42) responsible for neuroplasticity, neuroregeneration, survival and growth after spinal cord injury (SCI). Wistar rats were divided into four groups: (i) intact controls; (ii) 6 weeks of endurance training; (iii) SCI; (iv) pre-training + SCI. The animals survived for 6 weeks after SCI. Firstly, endurance training markedly upregulated mRNA expression and protein levels (up to four times) of growth factors (BDNF, GDNF) and their receptors (TrkB, Gfrα) in low thoracic segments (Th8–Th10) compared to levels in untrained animals. Secondly, we found that spontaneous neuroplasticity seen in the SCI alone group was GF-specific and was activated through both PLCγ-PKC and PLC-CAMKII signaling pathways. In addition, training prior to SCI markedly increased the activity of PLCγ-PKC signaling at both transcript and protein levels at and around the lesion site. Similar effects were seen in expression of PI3k/Akt and Ras/Erk1/2 signaling responsible for cell survival and regeneration. Thirdly, rats which underwent physical activity prior to SCI were more active and had significantly better neurological scores at the 14th and 42nd days of survival. These results suggest that regular physical activity could play an important role after SCI, as it maintains increased expression of GFs in spinal cord tissue 6 weeks post-SCI. The BDNF- and/or BDNF + GDNF-dependent signaling pathways were significantly affected in pre-trained SCI animals. In contrast, GDNF-dependent Rac1-Cdc42 signaling was not involved in training-affected SCI response.
Intrasalivary Thymic Carcinoma: A Case Report and Literature Review
Authors: Kunc Michał , Kamieniecki Alexandra , Walczak Grzegorz , Nowicki Tomasz , Wasąg Bartosz , Mikaszewski Bogusław , Stodulski Dominik , Biernat Wojciech 
Published: November 2021

AbstractEctopic thymic carcinomas are rarely diagnosed in the thyroid gland, let alone in extrathyroid tissues. In the currently available literature, only five cases of extrathyroidal malignancies with thymic differentiation have been reported as arising in the major salivary glands. A 69-year-old female presented with a slow-growing palpable mass in the left parotid gland. Fine needle aspiration biopsy suggested metastatic cancer, whereas core needle biopsy revealed high-grade squamous cell carcinoma. The patient underwent left radical parotidectomy with selective ipsilateral lymph node dissection and subsequent radiation therapy. The surgical specimen was taken for histopathological examination. Microscopically, the tumor resembled thymic carcinoma. It was composed of large nests of squamoid cells with smooth contours, focally with a syncytial growth pattern, and accompanied by abundant lymphocytes with reactive lymphoid follicles. This appearance resembled a micronodular thymic carcinoma with lymphoid hyperplasia. Moreover, the tumor displayed expression of squamous markers (p40 and p63) and markers of thymic carcinoma (CD5 and CD117). Therefore, the final diagnosis of intrasalivary thymic carcinoma was rendered. The molecular analysis including next-generation sequencing demonstrated no variants of the strong, potential, or unknown clinical significance. The patient remains disease-free at 1-year follow-up. In the current case, we comprehensively present a clinical, microscopic, molecular, and radiological picture of CD5-positive squamous cell carcinoma of the parotid. We postulate that similar cases should be designated as intrasalivary thymic carcinoma analogically to similar thyroid tumors. Our case and the limited literature data indicate they should be distinguished from conventional squamous cell carcinoma of major salivary glands due to their rather favorable prognosis.
Weak UVB Irradiation Promotes Macrophage M2 Polarization and Stabilizes Atherosclerosis
Authors: Li Xin-Yun , Qin Tao , Zhang Peng-Fei , Yan Wen-jiang , Lei Ling-Li , Kuang Jiang-Ying , Li Hao-Dong , Zhang Wen-Cheng , Lu Xiao-Ting , Sun Yuan-Yuan 
Published: November 2021

AbstractAtherosclerosis (AS) is a chronic cardiovascular disease endangering human health and is one of the most common causes of myocardial infarction and stroke. Macrophage polarization plays a vital role in regulating plaque stability. As an important component of sunlight, ultraviolet B (UVB) has been proven to promote vitamin D and nitric oxide synthesis. This research used an AS model in ApoE−/− mice to study the effects of UVB on macrophage polarization and atherosclerotic plaque stability. In vitro, UVB irradiation increased arginase-I (Arg-I, M2 macrophage) and macrophage mannose receptor (CD206) expression, while the expression of inducible nitric oxide synthase (iNOS) (M1 macrophage) and CD86 was decreased. UVB promoted Akt phosphorylation in vitro. In vivo, UVB irradiation promoted the stabilization of atherosclerotic lesion plaques, while the phenotype of M2 macrophages increased. Our research provides new evidence for UVB in preventing and treating atherosclerosis.
Hermeneutics, Practical Wisdom, and Cognitive Poetics
Authors: Zheng Yi 
Published: November 2021

AbstractIt may seem trivial to stress that our background knowledge is essential for literary interpretation, but what about practical wisdom, theinarticulablebackground knowledge? Can we articulate all the things that we know and are able to do in literary interpretation? Are we fully aware of all the assumptions behind our literary arguments? Instead of generally reflecting the status of hermeneutics at a macro-level, this essay argues that one way for hermeneutics to remain meaningful today is not to be tried as a theoretical whole, but as a source of sporadic inspiring arguments. To show that, at a micro-level, we can evaluate the strength of these arguments case by case without generalizing, we analyze from a cognitive perspective Gadamer’s argument that practical wisdom is crucial for literary interpretation. Using cognitive science to provide insights for literary study does not make the latter subservient to the former. Rather, cognitive poetics is a two-way street where each field complements the other by providing hypotheses and functioning as a testing ground. By demonstrating that we know more than we can tell in literary interpretation and that the three features Aristotle and Gadamer attribute to practical wisdom (contingent, inarticulable, and only learnable through experience) are at least tentatively empirically justified, this essay argues that hermeneutics has offered a noteworthy example for the two-way street of cognitive poetics.
Information Geometry of Reversible Markov Chains
Authors: Wolfer Geoffrey , Watanabe Shun 
Published: November 2021

AbstractWe analyze the information geometric structure of time reversibility for parametric families of irreducible transition kernels of Markov chains. We define and characterize reversible exponential families of Markov kernels, and show that irreducible and reversible Markov kernels form both a mixture family and, perhaps surprisingly, an exponential family in the set of all stochastic kernels. We propose a parametrization of the entire manifold of reversible kernels, and inspect reversible geodesics. We define information projections onto the reversible manifold, and derive closed-form expressions for the e-projection and m-projection, along with Pythagorean identities with respect to information divergence, leading to some new notion of reversiblization of Markov kernels. We show the family of edge measures pertaining to irreducible and reversible kernels also forms an exponential family among distributions over pairs. We further explore geometric properties of the reversible family, by comparing them with other remarkable families of stochastic matrices. Finally, we show that reversible kernels are, in a sense we define, the minimal exponential family generated by the m-family of symmetric kernels, and the smallest mixture family that comprises the e-family of memoryless kernels.
Optimized Runge-Kutta Methods with Automatic Step Size Control for Compressible Computational Fluid Dynamics
Authors: Ranocha Hendrik , Dalcin Lisandro , Parsani Matteo , Ketcheson David I. 
Published: November 2021

AbstractWe develop error-control based time integration algorithms for compressible fluid dynamics (CFD) applications and show that they are efficient and robust in both the accuracy-limited and stability-limited regime. Focusing on discontinuous spectral element semidiscretizations, we design new controllers for existing methods and for some new embedded Runge-Kutta pairs. We demonstrate the importance of choosing adequate controller parameters and provide a means to obtain these in practice. We compare a wide range of error-control-based methods, along with the common approach in which step size control is based on the Courant-Friedrichs-Lewy (CFL) number. The optimized methods give improved performance and naturally adopt a step size close to the maximum stable CFL number at loose tolerances, while additionally providing control of the temporal error at tighter tolerances. The numerical examples include challenging industrial CFD applications.
Study on Horizon Scanning by Citation Network Analysis and Text Mining: A Focus on Drug Development Related to T Cell Immune Response
Authors: Fujii Erika , Takata Takuya , Yamano Hiroko , Honma Masashi , Shimokawa Masafumi , Sasaki Hajime , Shikano Mayumi 
Published: November 2021

AbstractCertain innovative technologies applied to medical product development require novel evaluation approaches and/or regulations. Horizon scanning for such technologies will help regulators prepare, allowing earlier access to the product for patients and an improved benefit/risk ratio. This study investigates whether citation network analysis and text mining of scientific papers could be a tool for horizon scanning in the field of immunology, which has developed over a long period, and attempts to grasp the latest research trends. As the result of the analysis, the academic landscape of the immunology field was identified by classifying 90,450 papers (obtained from PubMED) containing the keyword “immune* and t lymph*” into 38 clusters. The clustering was indicative of the research landscape of the immunology field. To confirm this, immune checkpoint inhibitors were used as a retrospective test topic of therapeutics with new mechanisms of action. Retrospective clustering around immune checkpoint inhibitors was found, supporting this approach. The analysis of the research trends over the last 3 to 5 years in this field revealed several candidate topics, including ARID1A gene mutation, CD300e, and tissue resident memory T cells, which shows notable progress and should be monitored for future possible product development. Our results have demonstrated the possibility that citation network analysis and text mining of scientific papers can be a useful objective tool for horizon scanning of life science fields such as immunology.
Study on Horizon Scanning with a Focus on the Development of AI-Based Medical Products: Citation Network Analysis
Authors: Takata Takuya , Sasaki Hajime , Yamano Hiroko , Honma Masashi , Shikano Mayumi 
Published: November 2021

AbstractHorizon scanning for innovative technologies that might be applied to medical products and requires new assessment approaches to prepare regulators, allowing earlier access to the product for patients and an improved benefit/risk ratio. The purpose of this study is to confirm that citation network analysis and text mining for bibliographic information analysis can be used for horizon scanning of the rapidly developing field of AI-based medical technologies and extract the latest research trend information from the field. We classified 119,553 publications obtained from SCI constructed with the keywords “conventional,” “machine-learning,” or “deep-learning" and grouped them into 36 clusters, which demonstrated the academic landscape of AI applications. We also confirmed that one or two close clusters included the key articles on AI-based medical image analysis, suggesting that clusters specific to the technology were appropriately formed. Significant research progress could be detected as a quick increase in constituent papers and the number of citations of hub papers in the cluster. Then we tracked recent research trends by re-analyzing “young” clusters based on the average publication year of the constituent papers of each cluster. The latest topics in AI-based medical technologies include electrocardiograms and electroencephalograms (ECG/EEG), human activity recognition, natural language processing of clinical records, and drug discovery. We could detect rapid increase in research activity of AI-based ECG/EEG a few years prior to the issuance of the draft guidance by US-FDA. Our study showed that a citation network analysis and text mining of scientific papers can be a useful objective tool for horizon scanning of rapidly developing AI-based medical technologies.