bluuebunny/crossref_metadata_2025_split huggingface dataset:
A speed preserving Hilbert gradient flow for generalized integral Menger curvature
Authors: Knappmann Jan , Schumacher Henrik , Steenebrügge Daniel , von der Mosel Heiko 
Published: January 2022

Abstract
We establish long-time existence for a projected Sobolev gradient flow of generalized integral Menger curvature in the Hilbert case and provide

C

1
,
1

C^{1,1}

-bounds in time for the solution that only depend on the initial curve.
The self-avoidance property of integral Menger curvature guarantees that the knot class of the initial curve is preserved under the flow, and the projection ensures that each curve along the flow is parametrized with the same speed as the initial configuration.
Finally, we describe how to simulate this flow numerically with substantially higher efficiency than in the corresponding numerical

L
2

L^{2}

gradient descent or other optimization methods.
An orbit determination method of spacecraft based on distribution regression
Authors: Jiang Chunsheng 
Published: January 2022

Abstract
A new method of orbit determination (OD) is proposed: distribution regression. The paper focuses on the process of using sparse observation data to determine the orbit of the spacecraft without any prior information. The standard regression process is to learn a map from real numbers to real numbers, but the approach put forward in this paper is to map from probability distributions to real-valued responses. According to the new algorithm, the number of orbital elements can be predicted by embedding the probability distribution into the reproducing kernel Hilbert space. While making full use of the edge of big data, it also avoids the problem that the algorithm cannot converge due to improper initial values in precise OD. The simulation experiment proves the effectiveness, robustness, and rapidity of the algorithm in the presence of noise in the measurement data.
The risk factors of COVID-19 in 50–74 years old people: a longitudinal population-based study
Authors: Hozhabr Jamali Atergeleh , Emamian Mohammad Hassan , Goli Shahrbanoo , Rohani-Rasaf Marzieh , Hashemi Hassan , Fotouhi Akbar 
Published: January 2022

Abstract

Objectives
To investigate the risk factors of COVID-19 infection in a longitudinal study of a population aged 50–74 years.

Methods
Data were collected from Shahroud Eye Cohort study and the COVID-19 electronic registry in Shahroud, northeast Iran. Participants were followed for about 13 months and predisposing factors for COVID-19 infection were investigated using log binominal model and calculating relative risks.

Results
From the beginning of the COVID-19 outbreak in Shahroud (February 20, 2020) to March 26, 2021, out of 4,394 participants in the Eye Cohort study, 271 (6.1%) were diagnosed with COVID-19 with a positive reverse transcription polymerase chain reaction test on two nasopharyngeal and oropharyngeal swabs. Risk factors for COVID-19 infection included male gender (relative risk (RR) = 1.51; 95% confidence intervals (CI), 1.15–1.99), body mass index (BMI) over 25 (RR = 1.03; 95% CI, 1.01–1.05), and diabetes (RR = 1.31; 95% CI, 1.02–1.67). Also, smoking (RR = 0.51; 95% CI, 0.28–0.93) and education (RR = 0.95; 95% CI, 0.92–0.98) showed inverse associations.

Conclusions
Men, diabetics, and those with BMI over 25 should be more cognizant and adhere to health protocols related to COVID-19 prevention and should be given priority for vaccination.
Kinetic study on the reaction between Incoloy 825 alloy and low-fluoride slag for electroslag remelting
Authors: Ju Jiantao , Zhu Zhihong , An Jialiang , Yang Kangshuai , Gu Yue 
Published: January 2022

Abstract
A kinetic model for the reactions between the low-fluoride slag CaF2–CaO–Al2O3–MgO–Li2O–TiO2 and Incoloy 825 alloy was proposed based on the two-film theory. The applicability of the model was verified to predict the variation of components in the slag–metal reaction process. The results show that the controlling step of the reaction 4[Al] + 3(TiO2) = 3[Ti] + 2(Al2O3) is the mass transfer of Al and Ti in the liquid alloy and the controlling step of the reactions 4[Al] + 3(SiO2) = 3[Si] + 2(Al2O3) and [Si] + (TiO2) = [Ti] + (SiO2) is the mass transfer of SiO2 in the molten slag. With increasing TiO2 content in the slag from 3.57% to 11.27%, the Al content in the alloy decreased whereas the Ti content increased gradually. The Si content continued to decrease during the slag–metal reaction. Soluble oxygen in the alloy reacts with Al, Ti, and Si, resulting in a decrease of the oxygen content in the alloy. The variations of TiO2 content were in good agreement with the calculated results by the kinetic model whereas the measured results of Al2O3 and SiO2 in the slag were lower than the calculated results, which is mainly due to the volatilization of fluoride.
A Generalized Non-Parametric Instrumental Variable-Control Function Approach to Estimation in Nonlinear Settings
Authors: Kim Kyoo il , Petrin Amil 
Published: January 2022

Abstract
When the endogenous variables enter non-parametrically into the regression equation standard linear instrumental variables approaches fail. Two existing solutions are the non-parametric instrumental variables (NPIVs) estimators, which are based on a set of conditional moment restrictions (CMRs), and the control function (CF) estimators, which use conditional mean independence (CMI) restrictions. Our first contribution is to show that – similar to CMI – the CMR place shape restrictions on the conditional expectation of the error given the instruments and endogenous variables that are sufficient for identification, and we call our new estimator based on these restrictions the CMR-CF estimator. Our second contribution is to develop an estimator for non-linear and non-parametric settings that can combine both CMR and CMI restrictions, which cannot be done in either the NPIV nor the non-parametric CF setting. This new “Generalized CMR-CF” uses both CMR and CMI restrictions together by allowing the conditional expectation of the structural error to depend on both instruments and control variables. When sieves are used to approximate both the structural function and the CF our estimator reduces to a series of least squares regressions. Our Monte Carlos illustrate that our new estimator performs well across several economic settings.
On the self-similarity index of 𝑝-adic analytic pro-𝑝 groups
Authors: Noseda Francesco , Snopce Ilir 
Published: January 2022

Abstract
Let 𝑝 be a prime.
We say that a pro-𝑝 group is self-similar of index

p
k

p^{k}

if it admits a faithful self-similar action on a

p
k

p^{k}

-ary regular rooted tree such that the action is transitive on the first level.
The self-similarity index of a self-similar pro-𝑝 group 𝐺 is defined to be the least power of 𝑝, say

p
k

p^{k}

, such that 𝐺 is self-similar of index

p
k

p^{k}

.
We show that, for every prime

p
⩾
3

p\geqslant 3

and all integers 𝑑, there exist infinitely many pairwise non-isomorphic self-similar 3-dimensional hereditarily just-infinite uniform pro-𝑝 groups of self-similarity index greater than 𝑑.
This implies that, in general, for self-similar 𝑝-adic analytic pro-𝑝 groups, one cannot bound the self-similarity index by a function that depends only on the dimension of the group.
Completely bounded homomorphisms of the Fourier algebra revisited
Authors: Daws Matthew 
Published: January 2022

Abstract
Assume that

A
⁢

(
G
)

A(G)

and

B
⁢

(
H
)

B(H)

are the Fourier and Fourier–Stieltjes algebras of locally compact groups 𝐺 and 𝐻, respectively.
Ilie and Spronk have shown that continuous piecewise affine maps

α
:

Y
⊆
H
→
G

\alpha\colon Y\subseteq H\to G

induce completely bounded homomorphisms

Φ
:

A
⁢

(
G
)

→

B
⁢

(
H
)

\Phi\colon A(G)\to B(H)

and that, when 𝐺 is amenable, every completely bounded homomorphism arises in this way.
This generalised work of Cohen in the abelian setting.
We believe that there is a gap in a key lemma of the existing argument, which we do not see how to repair.
We present here a different strategy to show the result, which instead of using topological arguments, is more combinatorial and makes use of measure-theoretic ideas, following more closely the original ideas of Cohen.
Estimating adsorption isotherm parameters in chromatography via a virtual injection promoting double feed-forward neural network
Authors: Xu Chen , Zhang Ye 
Published: January 2022

Abstract
The means to obtain the adsorption isotherms is a fundamental open problem in competitive chromatography.
A modern technique of estimating adsorption isotherms is to solve a nonlinear inverse problem in a partial differential equation so that the simulated batch separation coincides with actual experimental results.
However, this identification process is usually ill-posed in the sense that the uniqueness of adsorption isotherms cannot be guaranteed, and moreover, the small noise in the measured response can lead to a large fluctuation in the traditional estimation of adsorption isotherms.
The conventional mathematical method of solving this problem is the variational regularization, which is formulated as a non-convex minimization problem with a regularized objective functional.
However, in this method, the choice of regularization parameter and the design of a convergent solution algorithm are quite difficult in practice.
Moreover, due to the restricted number of injection profiles in experiments, the types of measured data are extremely limited, which may lead to a biased estimation.
In order to overcome these difficulties, in this paper, we develop a new inversion method – the virtual injection promoting double feed-forward neural network (VIP-DFNN).
In this approach, the training data contain various types of artificial injections and synthetic noisy measurement at outlet, generated by a conventional physics model – a time-dependent convection-diffusion system.
Numerical experiments with both artificial and real data from laboratory experiments show that the proposed VIP-DFNN is an efficient and robust algorithm.
Secant-type iteration for nonlinear ill-posed equations in Banach space
Authors: George Santhosh , Sreedeep C. D. , Argyros Ioannis K. 
Published: January 2022

Abstract
In this paper, we study secant-type iteration for nonlinear ill-posed equations involving 𝑚-accretive mappings in Banach spaces.
We prove that the proposed iterative scheme has a convergence order at least 2.20557 using assumptions only on the first Fréchet derivative of the operator.
Further, using a general Hölder-type source condition, we obtain an optimal error estimate.
We also use the adaptive parameter choice strategy proposed by Pereverzev and Schock (2005) for choosing the regularization parameter.
Diffusion tensor regularization with metric double integrals
Authors: Frischauf Leon , Melching Melanie , Scherzer Otmar 
Published: January 2022

AbstractIn this paper, we propose a variational regularization method for denoising and inpainting of diffusion tensor magnetic resonance images. We consider these images as manifold-valued Sobolev functions, i.e. in an infinite dimensional setting, which are defined appropriately. The regularization functionals are defined as double integrals, which are equivalent to Sobolev semi-norms in the Euclidean setting. We extend the analysis of [14] concerning stability and convergence of the variational regularization methods by a uniqueness result, apply them to diffusion tensor processing, and validate our model in numerical examples with synthetic and real data.
The effectiveness of the metabolic map in promoting meaningful learning
Authors: Gromley Zeynep , Agwuncha Chinelo , Nahar Vinayak K. , Gromley Adam 
Published: January 2022

Abstract

Context
Many medical students and practicing physicians view biochemistry, especially its metabolic pathways, as a challenging topic given the depth of material. Medical biochemistry educators aim to help prepare future physicians to apply knowledge of metabolism to disease processes. Research confirms that study tools promote critical thinking and help to connect biochemistry concepts to health and disease processes.

Objectives
To explore whether the Pathways of Human Metabolism Map as a study tool helps to connect basic metabolic pathways to clinical applications.

Methods
We provided the Pathways of Human Metabolism Map to our first-year osteopathic medical students and conducted a survey to assess their perceptions. Our survey questions aimed to explore the effectiveness of utilizing the metabolic map for connecting the basic metabolic pathways to clinical applications on their studies. Students were surveyed at the end of the course utilizing a Qualtrics survey encompassing Likert scale questions as well as open-ended responses.

Results
The results of our comprehensive survey questions revealed the unique perceptions of students. Analysis of our data implicates that study tools like the metabolic map inspire meaningful learning.

Conclusions
Our data show that students who utilized the metabolic map in their studies reported that utilizing the map improved their understanding of medical biochemistry. Our research results suggest that providing study aids like the metabolic map encourages students to minimize rote memorization and promotes integration with clinical context. Our results provide a support for study strategies that implement meaningful learning in medical education.
Assessment of COVID-19 mRNA vaccination titer and side effects in healthy volunteers
Authors: Kozakai Rikei , Kushida Akira , Adjou Moumouni Paul Franck Adeyissimi , Okuma Sadatsugu , Takahashi Kazuya , Hoshi Kuniko , Sato Yuri , Takahashi Mizue , Chida Nodoka , Takahashi Mei , Iwabuchi Shukuko , Izumi Yoshihiko , Fukami Kana , Nakashiro Shuji , Nojima Hisashi , Takahashi Shinichiro 
Published: January 2022

Abstract

Objectives
An effective vaccine against SARS-CoV-2 is essential to mitigate the COVID-19 pandemic. In these several months, a number of groups have started to report humoral responses and side effects after BNT162b2 vaccinations. Although these reports demonstrate the safety and efficacy, further studies are warranted to verify these findings. Here we examined the levels of SARS-CoV-2 antibodies in Japanese healthy volunteers who underwent BNT162b2 vaccine, to assess the humoral responses and side effects.

Methods
Forty-one healthy volunteers’ samples were used for the measurement of SARS-CoV-2 antibodies with chemiluminescent assays against the Receptor Binding Domain (RBD) of the virus. We also measured the side effects of the vaccination.

Results
Although the levels of IgM varied, all participants were seronegative for IgM and IgG before vaccination, and both IgM and IgG were significantly increased after the vaccinations. We further analyzed the humoral responses in relation to age, and found that the IgG levels for 14 days and 35 days, and IgM levels for 14 days after vaccination showed clear declining trends with age. Commonly reported side effects in the participants were sore arm/pain (90.0%) after the first dose, and generalized weakness/fatigue (70.0%), fever (57.5%), and sore arm/pain (90.0%) after the second dose.

Conclusions
BNT162b2 vaccination generates sufficient production of IgG especially after the second dose, though the response decreases age-dependently. The high frequencies of generalized weakness/fatigue, fever, and sore arm/pain were not negligible, especially after the second dose. This may be associated with the age characteristics of the population.
Intelligent electromagnetic metasurface camera: system design and experimental results
Authors: Wang Zhuo , Zhang Hongrui , Zhao Hanting , Cui Tie Jun , Li Lianlin 
Published: January 2022

Abstract
Electromagnetic (EM) sensing is uniquely positioned among nondestructive examination options, which enables us to see clearly targets, even when they visually invisible, and thus has found many valuable applications in science, engineering and military. However, it is suffering from increasingly critical challenges from energy consumption, cost, efficiency, portability, etc., with the rapidly growing demands for the high-quality sensing with three-dimensional high-frame-rate schemes. To address these difficulties, we propose the concept of intelligent EM metasurface camera by the synergetic exploitation of inexpensive programmable metasurfaces with modern machine learning techniques, and establish a Bayesian inference framework for it. Such EM camera introduces the intelligence over the entire sensing chain of data acquisition and processing, and exhibits good performance in terms of the image quality and efficiency, even when it is deployed in highly noisy environment. Selected experimental results in real-world settings are provided to demonstrate that the developed EM metasurface camera enables us to see clearly human behaviors behind a 60 cm-thickness reinforced concrete wall with the frame rate in order of tens of Hz. We expect that the presented strategy could have considerable impacts on sensing and beyond, and open up a promising route toward smart community and beyond.
Optical metasurfaces towards multifunctionality and tunability
Authors: Du Kang , Barkaoui Hamdi , Zhang Xudong , Jin Limin , Song Qinghai , Xiao Shumin 
Published: January 2022

Abstract
Optical metasurfaces is a rapidly developing research field driven by its exceptional applications for creating easy-to-integrate ultrathin planar optical devices. The tight confinement of the local electromagnetic fields in resonant photonic nanostructures can boost many optical effects and offer novel opportunities for the nanoscale control of light–matter interactions. However, once the structure-only metasurfaces are fabricated, their functions will be fixed, which limits it to make breakthroughs in practical applications. Recently, persistent efforts have led to functional multiplexing. Besides, dynamic light manipulation based on metasurfaces has been demonstrated, providing a footing ground for arbitrary light control in full space-time dimensions. Here, we review the latest research progress in multifunctional and tunable metasurfaces. Firstly, we introduce the evolution of metasurfaces and then present the concepts, the basic principles, and the design methods of multifunctional metasurface. Then with more details, we discuss how to realize metasurfaces with both multifunctionality and tunability. Finally, we also foresee various future research directions and applications of metasurfaces including innovative design methods, new material platforms, and tunable metasurfaces based metadevices.
The crystal structure of 4-phenyl-4-[2-(pyridine-4-carbonyl)hydrazinylidene]butanoic acid, C16H15N3O3
Authors: Setshedi Itumeleng B. , Smith Mark G. 
Published: January 2022

Abstract
C16H15N3O3, monoclinic, P21/c (no. 14), a = 9.4957(3) Å, b = 18.2275(5) Å, c = 9.0896(3) Å, β = 114.372(1)°, V = 1433.05(15) Å3, Z = 4, R

gt
(F) = 0.0380, wR

ref
(F
2) = 0.1011, T = 173 K.
Crystal structure of 2-((4-phenyl-5-(pyridin-4-yl)-4H-1,2,4-triazol-3-yl)thio)acetonitrile, C15H11N5S
Authors: Sun Guo-Xiang , Min Li-Jing , Han Liang , Liu Xing-Hai 
Published: January 2022

Abstract
C15H11N5S, orthorhombic, Pbca (no. 61), a = 9.7864(2) Å, b = 15.5709(3) Å, c = 18.7774(4) Å, V = 2861.36(10) Å3, Z = 8, R

gt
(F) = 0.0485, wR

ref
(F
2) = 0.1390, T = 296.15 K.
The crystal structure of (E)-3-chloro-2-(2-(4-methylbenzylidene)hydrazinyl)pyridine, C13H12ClN3
Authors: Sun Guo-Xiang , Min Li-Jing , Han Liang , Liu Xing-Hai 
Published: January 2022

Abstract
C13H12ClN3, orthorhombic, Fdd2 (no. 43), a = 28.7760(11) Å, b = 41.7393(17) Å, c = 8.5929(3) Å, V = 10,320.8(7) Å3, Z = 32, R

gt
(F) = 0.0477, wR

ref
(F
2) = 0.0976, T = 296 K.
The crystal structure of 2-(2-methyl-6-phenyl-4H-pyran-4-ylidene)-1H-indene-1,3(2H)-dione, C21H14O3
Authors: Sun An-Na , Huang Xiao-Bo , Wu Deng-Ze 
Published: January 2022

Abstract
C21H14O3, monoclinic, P21/c (no. 14), a = 4.8318(8) Å, b = 26.590(4) Å, c = 11.821(2) Å, β = 91.050(4)°, V = 1518.4(4) Å3, Z = 4, R

gt
(F) = 0.0401, wR

ref
(F) = 0.1038, T = 296(2) K.

CCDC no.: 2122345
Novel solitons solutions of two different nonlinear PDEs appear in engineering and physics
Authors: Ullah Naeem , Asjad Muhammad Imran , Ur Rehman Hamood 
Published: January 2022

Abstract
In this piece of research, our aim is to investigate the novel solitons solutions of nonlinear (4+1)-dimensional Fokas equation (FE) and (2+1)-dimensional Breaking soliton equation (BSE) via new extended direct algebraic method. New acquired solutions are bright, singular, dark, periodic singular, combined dark-bright and combined dark-singular solitons along with hyperbolic and trigonometric functions solutions. We achieved different kinds of solitons solutions contain key applications in engineering and physics. By taking the appropriate values of these parameters, numerous novel structures are also plotted. These solutions define the wave performance of the governing models, actually. Furthermore, the physical understanding of the acquired solutions is revealed in forms of 3-D, 2-D and contour graphs for different appropriate parameters. From results, we conclude that the applied computational method is straight, talented and can be applied in more complex phenomena for such models.
Modal characteristics of harmonic gear transmission flexspline based on orthogonal design method
Authors: Wei Leyu , Yang Jie , Wang Changlu , Wang Xingxing , Liu Xinmeng 
Published: January 2022

Abstract
The flexspline features several modal characteristics that are related to its structural parameters, which could impose an impact on the stability and reliability of the system of harmonic gear transmission. In this article, we have integrated the method of orthogonal design with the approach of finite element, so as to study the modal characteristics of flexspline under varying structural parameters. Furthermore, we have analyzed the ways of how varying structural parameters could impose an impact on the first eight-order natural frequencies of flexspline. In addition, by adopting the method of range and variance analysis for the obtained data, we have examined the influence imposed by varying structural parameters on the modal characteristics of flexspline, which could lay a foundation for the optimal design of the structural parameters of flexspline.
Advances in heterocycles as DNA intercalating cancer drugs
Authors: Das Aparna , Banik Bimal Krishna 
Published: January 2022

Abstract
The insertion of a molecule between the bases of DNA is known as intercalation. A molecule is able to interact with DNA in different ways. DNA intercalators are generally aromatic, planar, and polycyclic. In chemotherapeutic treatment, to suppress DNA replication in cancer cells, intercalators are used. In this article, we discuss the anticancer activity of 10 intensively studied DNA intercalators as drugs. The list includes proflavine, ethidium bromide, doxorubicin, dactinomycin, bleomycin, epirubicin, mitoxantrone, ellipticine, elinafide, and echinomycin. Considerable structural diversities are seen in these molecules. Besides, some examples of the metallo-intercalators are presented at the end of the chapter. These molecules have other crucial properties that are also useful in the treatment of cancers. The successes and limitations of these molecules are also presented.