bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using machine learning model explanations to identify proteins related to severity of meibomian gland dysfunction
Authors: Storås Andrea M. , Fineide Fredrik , Magnø Morten , Thiede Bernd , Chen Xiangjun , Strümke Inga , Halvorsen Pål , Galtung Hilde , Jensen Janicke L. , Utheim Tor P. , Riegler Michael A. 
Published: December 2023

AbstractMeibomian gland dysfunction is the most common cause of dry eye disease and leads to significantly reduced quality of life and social burdens. Because meibomian gland dysfunction results in impaired function of the tear film lipid layer, studying the expression of tear proteins might increase the understanding of the etiology of the condition. Machine learning is able to detect patterns in complex data. This study applied machine learning to classify levels of meibomian gland dysfunction from tear proteins. The aim was to investigate proteomic changes between groups with different severity levels of meibomian gland dysfunction, as opposed to only separating patients with and without this condition. An established feature importance method was used to identify the most important proteins for the resulting models. Moreover, a new method that can take the uncertainty of the models into account when creating explanations was proposed. By examining the identified proteins, potential biomarkers for meibomian gland dysfunction were discovered. The overall findings are largely confirmatory, indicating that the presented machine learning approaches are promising for detecting clinically relevant proteins. While this study provides valuable insights into proteomic changes associated with varying severity levels of meibomian gland dysfunction, it should be noted that it was conducted without a healthy control group. Future research could benefit from including such a comparison to further validate and extend the findings presented here.
Two‐stage architectural fine‐tuning for neural architecture search in efficient transfer learning
Authors: Park Soohyun , Son Seok Bin , Lee Youn Kyu , Jung Soyi , Kim Joongheon 
Published: December 2023

AbstractIn many deep neural network (DNN) applications, the difficulty of gathering high‐quality data in industry fields hinders the practical use of DNN. Thus, the concept of transfer learning (TL) has emerged, which leverages the pretrained knowledge of the DNN which was built based on large‐scale datasets. For this TL objective, this paper suggests two‐stage architectural fine‐tuning for reducing the costs and time while exploring the most efficient DNN model, inspired by neural architecture search (NAS). The first stage is mutation, which reduces the search costs using a priori architectural information. Moreover, the next stage is early‐stopping, which reduces NAS costs by terminating the search process in the middle of computation. The data‐intensive experimental results verify that the proposed method outperforms benchmarks.
The effect of pressure-anisotropy-driven kinetic instabilities on magnetic field amplification in galaxy clusters
Authors: Rappaz Y. , Schober J. 
Published: December 2023

Context. The intracluster medium (ICM) is the low-density diffuse gas that fills the space between galaxies within galaxy clusters. It is primarily composed of magnetized plasma, which reaches virial temperatures of up to 108 K, probably due to mergers of subhalos. Under these conditions, the plasma is weakly collisional and therefore has an anisotropic pressure tensor with respect to the local direction of the magnetic field. This triggers very fast, Larmor-scale, pressure-anisotropy-driven kinetic instabilities that alter magnetic field amplification.
Aims. We aim to study magnetic field amplification through a turbulent, small-scale dynamo, including the effects of the kinetic instabilities, during the evolution of a typical massive galaxy cluster. A specific aim of this work is to establish a redshift limit from which a dynamo has to start to amplify the magnetic field up to equipartition with the turbulent velocity field at redshift z = 0.
Methods. We implemented one-dimensional radial profiles for various plasma quantities for merger trees generated with the modified GALFORM algorithm. We assumed that turbulence is driven by successive mergers of dark matter halos and constructed effective models for the Reynolds number Reeff dependence on the magnetic field in three different magnetization regimes (unmagnetized, magnetized “kinetic”, and magnetized “fluid”), including the effects of kinetic instabilities. The magnetic field growth rate is calculated for the different Reeff models.
Results. The model results in a higher magnetic field growth rate at higher redshift. For all scenarios considered in this study, to reach equipartition at z = 0, it is sufficient for the amplification of the magnetic field to start at redshift zstart ≈ 1.5 and above. The time to reach equipartition can be significantly shorter in cases with systematically smaller turbulent forcing scales and for the highest Reeff models.
Conclusions. The origin of magnetic fields in the weakly collisional ICM can be explained by the small-scale turbulent dynamo, provided that the dynamo process starts beyond a given redshift. Merger trees are useful tools for studying the evolution of magnetic fields in weakly collisional plasmas, and could also be used to constrain the different stages of the dynamo that could potentially be observed by future radio telescopes.
User-Centered Evaluation and Design Recommendations for an Internal Medicine Resident Competency Assessment Dashboard
Authors: Vennemeyer Scott , Kinnear Benjamin , Gao Andy , Zhu Siyi , Nattam Anunita , Knopp Michelle I. , Warm Eric , Wu Danny T.Y. 
Published: December 2023

Abstract
Objectives Clinical Competency Committee (CCC) members employ varied approaches to the review process. This makes the design of a competency assessment dashboard that fits the needs of all members difficult. This work details a user-centered evaluation of a dashboard currently utilized by the Internal Medicine Clinical Competency Committee (IM CCC) at the University of Cincinnati College of Medicine and generated design recommendations.
Methods Eleven members of the IM CCC participated in semistructured interviews with the research team. These interviews were recorded and transcribed for analysis. The three design research methods used in this study included process mapping (workflow diagrams), affinity diagramming, and a ranking experiment.
Results Through affinity diagramming, the research team identified and organized opportunities for improvement about the current system expressed by study participants. These areas include a time-consuming preprocessing step, lack of integration of data from multiple sources, and different workflows for each step in the review process. Finally, the research team categorized nine dashboard components based on rankings provided by the participants.
Conclusion We successfully conducted user-centered evaluation of an IM CCC dashboard and generated four recommendations. Programs should integrate quantitative and qualitative feedback, create multiple views to display these data based on user roles, work with designers to create a usable, interpretable dashboard, and develop a strong informatics pipeline to manage the system. To our knowledge, this type of user-centered evaluation has rarely been attempted in the medical education domain. Therefore, this study provides best practices for other residency programs to evaluate current competency assessment tools and to develop new ones.
Research on the flow-induced vibration characteristics based on heat–fluid–structure coupling in natural gas loop
Authors: Qiu Yilong , Ren Jia , Zhang Xi , Chen Siyu 
Published: December 2023

To research the flow-induced vibration characteristics of the natural gas loop, unsteady numerical simulation is carried out on the loop calculation model under different ambient temperatures and different flow rates, and the influence of different flow rates on the dynamic characteristics of the flow field and its induced vibration characteristics is obtained. The results show that the inherent frequency of the natural gas loop increases slightly under the action of heat–fluid–solid coupling. The maximum equivalent stress of the loop increases with the increase in ambient temperature under low flow conditions, but it is almost constant under high flow conditions. The smaller the cross-sectional area of the loop pipeline inlet, the greater the pressure, and the more significant the pressure gradient along the flow direction. The pressure pulsation of monitoring points in the pipeline under different flow rates presents different rules, and the pulsation amplitude of pipes with different diameters is different, among which the amplitude of the pipe with a diameter of 250 mm is the largest and that of the pipe with a diameter of 150 mm is the smallest. The pressure pulsation signals are concentrated in the low-frequency band of 0–10 Hz, and the range of the band decreases with the increase in the flow rate. The vibration frequency of the loop structure is close to the fluid pressure pulsation frequency and the inherent frequency under the action of heat–fluid–solid coupling, which causes a resonance of about 2 Hz.
“You look like my 14-year-old daughter”
Authors: Wang Wanwen , Ngai Jonathan 
Published: December 2023

Abstract
The main purpose of this corpus-based study is to examine the different types of sexist language women are
subjected to in their daily interactions with men, together with their hidden ideologies. To this end, we analysed a total of
1,118 English tweets posted on the hashtag #everydaysexism on Twitter over a year. Results indicate that women experience both
overt and indirect verbal aggression in different domains of life, expressed through a range of sexist linguistic markers, and
that such aggression often reflect the users’ beliefs and values about men and women. By using a category-based model to examine a
feminist narrative hashtag where women’s experiences of sexism are shared, our study offers a robust and principled approach to
conducting a corpus-based, cross-domain discourse analysis of sexism in daily communication.
Theoretical design of uncooled mid-infrared PbSe P+pBn+ barrier detectors
Authors: Su Leisheng , Liu Yun , Zhang Heqiu , Yang Yiming , Qiu Jijun 
Published: December 2023

Abstract
A novel uncooled mid-wavelength infrared (MWIR) P+pBn+ barrier detector based on epitaxial PbSe absorber layer on Ge substrate is theoretically investigated by finite element analysis in order to achieve optimal detection performance. The simulated results show that the P+pBn+ barrier architecture can further effectively reduce the room-temperature dark current to 4.45 mA cm−2 under −0.1 V bias, which is 12 times lower than a PbSe pBn+ unipolar barrier device in a previous study. Moreover, the P+pBn+ barrier architecture exhibits excellent responsivity and detectivity of 1.83 A W −1 and 3.23 × 1010 cm Hz1/2 W−1 at 3.8 μm, respectively. These results suggest that this P+pBn+ barrier detector based on natural MBE epitaxy technology could have potential in the emerging high-sensitivity and high-detectivity uncooled MWIR applications.
Research on satellite laser ranging observation task scheduling method
Authors: Zequn Lv , Ning An , Cunbo Fan , Chengzhi Liu , Zhenwei Li , Jian Gao , Guanyu Wen , Xue Dong 
Published: December 2023

Abstract
Satellite laser ranging (SLR) is a technology with the highest precision of single measurement of satellite radial distance, which is developing rapidly in the direction of long-distance, high-precision and automation. SLR autonomous observation task scheduling is an important step in realizing station automation, which needs to satisfy the principles of satellite tracking priority and maximization of observation revenue at the same time. In order to improve the automation and intelligence level of SLR system, based on the framework of ant colony optimization (ACO) algorithm, this paper combines the dynamic optimization characteristics of ACO algorithm and the local optimization characteristics of greedy algorithm, introduces the maximum-minimum ant mechanism, and puts forward a scheduling scheme for SLR observation task based on greedy ant colony algorithm (GACA). The results show that compared with the current scheduling method applied in practice, the number of observation satellites obtained from the GACA algorithm-based observation task planning for the SLR system has been improved by 37.4%, the total arc segment of satellite observation with higher priority has been extended by 36.47%, and the total observation gain has been increased by 42.39% in the same period of time. It effectively solves the problems of low efficiency, easy to miss satellites (being equipped with corner-cubes) and less satellites (being equipped with corner-cubes) stars in the observation process in manual scheduling, and provides a simple, practical, efficient and convenient observation task planning scheme for the establishment of an unmanned SLR system.
Universal embedding of autonomous dynamical systems into a Lotka-Volterra-like format
Authors: Frezzato Diego 
Published: December 2023

Abstract
We show that the ordinary differential equations (ODEs) of any deterministic autonomous dynamical system with continuous and bounded rate-field components can be embedded into a quadratic Lotka-Volterra-like form by turning to an augmented set of state variables. The key step consists in expressing the rate equations by employing the Universal Approximation procedure (borrowed from the machine learning context) with logistic sigmoid ‘activation function’. Then, by applying already established methods, the resulting ODEs are first converted into a multivariate polynomial form (also known as generalized Lotka-Volterra), and finally into the quadratic structure. Although the final system of ODEs has a dimension virtually infinite, the feasibility of such a universal embedding opens to speculations and calls for an interpretation at the physical level.
On the magnetic field in Earth’s interior
Authors: Provatidis Christopher G 
Published: December 2023

Abstract
This paper discusses the possible distribution of Earth’s magnetic field in its three main layers. As a first step, using the IGRF-13 model, it was found that the magnetic field energy exterior to the liquid outer core (i.e., inside the mantle and the surrounding Earth’s atmosphere) is about

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J (for epoch 2010) while the field strength exactly at the Core-Mantle-Boundary (CMB) is about 0.42 mT (RMS value). These findings can be further considered as reliable reference values among the large dispersion of published data for the total magnetic field in Earth’s interior. Therefore, utilizing the layer breakdown reported in a pioneering paper (Glatzmaier and Roberts [8]) according to which the inner core includes about 10% of the total energy content, it was made possible to validate a previously reported figure (year 1949: 9×1020 J) regarding the total magnetic field energy of the Earth. But due to substantial deviation of the latter from a later reported figure (year 1980: 7×1021 J), this paper continues the investigation for the purpose of clarifying the issue. In this context, two inverse-cubic dipole models and the bar magnet (tiny and cylindrical) model, as well as the IGRF-13 standard were applied and compared in the Earth’s interior. Overall, under certain conditions these findings are successfully compared with literature reports, and eventually (after many assumptions) reached an acceptable compromise regarding the spatial distribution of the magnetic field, while a stimulus for further reflection to other researchers was provided. At the end, a question is posed and somewhat answered whether the available magnetic field energy is abundant to feed the motion of futuristic lightweight electromagnetic vehicles revived in recent literature.
Rayleigh wave through half space semiconductor solid with temperature dependent properties
Authors: Saeed Tareq , Ali Khan Maaz , Alzahrani Ali Rashash R , Jahangir Adnan 
Published: December 2023

Abstract
The article focuses on Rayleigh wave propagation in a homogeneous isotropic semi-conductor thermoelastic medium rotating with fixed angular frequency with temperature-dependent properties. The elastic constants depend upon the temperature function. The effects of temperature dependency parameter, time derivative, and fractional order are illustrated. By the theory of thermo-elasticity, waves result in the generation of thermal signals that propagate through the medium. A heat conduction model of three-phase lag (3PL) along with fractional order time derivative is used to analyze the thermal signals. The secular equations of Rayleigh waves are derived mathematically at the stress-free, carrier density and thermally insulated boundaries. Some specific properties like velocity, attenuation coefficient, specific heat loss and penetration depth for Rayleigh waves have been evaluated and presented graphically. The secular equations are computed numerically and depicted graphically using Matlab.
Building Machine Learning Models to Improve Hypertension Diagnosis
Authors: Haynatzki Roman , Windle Thomas , Windle John 
Published: December 2023

Abstract
Hypertension (HT) is a major risk factor for heart disease, stroke, and kidney disease. A diagnosis of HT is based on two or more blood pressure (BP) readings taken on two or more visits, and such diagnosis may vary depending on the threshold BP values utilized by specific guidelines. Our hypertension identification approach has been recently proposed and validated for HT diagnosis and could be used as ground truth in modeling of latent HT diagnosis. Our approach to modeling of latent HT diagnosis with high precision will leverage analytics to “Big Data”, such as electronic health records (EHRs). In this work, we will review the time complexity underlying the classical ML methods XGBoost (XGB) and Artificial Neural Networks (ANN). In particular, we compare the XGB and ANN to leverage their strengths. The performance of all algorithms for diagnosing HT will be characterized using the area under the curve (AUC) approach on a big EHR longitudinal dataset. Predictor variable importance and model interpretability will be assessed using the Shapley values approach.
Temporal-causal modeling of air pollution in the city of Plovdiv, Bulgaria: a case study
Authors: Ivanov A V , Gocheva-Ilieva S G , Stoimenova-Minova M P 
Published: December 2023

Abstract
High levels of air pollution are dangerous to human health, which is a current problem for densely populated cities worldwide. Studying this problem can help detect pollutants’ time dependencies on basic meteorological measurements and other factors for future prediction and elaborate corresponding alarms when official upper pollution limits are exceeded. In this work, time-causal models based on previous daily time observations and meteorological measurements in the city of Plovdiv, Bulgaria, are applied. Vector-type temporal-causal models are constructed and analyzed for carbon dioxide (CO2), nitrogen dioxide (NO2), sulfur dioxide (SO2), and fine dust particles below size 10, 2.5, and 1 micron (PM10, PM2.5, and PM1), respectively. Pollution levels are predicted seven days ahead.
Christov expansion method for nonlocal nonlinear evolution equations
Authors: Christou M A , Christov I C 
Published: December 2023

Abstract
Christov functions are a complete orthonormal set of functions on L
2(-∞,∞) that allow us to expand derivatives, nonlinear products, and nonlocal (integro-differential) terms back into the same basis. These properties are beneficial when solving nonlinear evolution equations using Galerkin spectral methods. In this work, we demonstrate such a “Christov expansion method” for the Benjamin–Ono (BO) equation. In the BO equation, the dispersion term is nonlocal, given by the Hilbert transform of the second spatial derivative of the unknown function. The Hilbert transform of the Christov functions can be computed using complex integration and Cauchy’s residue theorem to obtain simple relations. Then, a Galerkin spectral expansion can be used to the solve the BO equation. Time integration is performed using a Crank–Nicolson-type scheme. Importantly, the Christov expansion method yields a banded matrix for the spatial discretization, even though the spatial terms are nonlocal. To demonstrate the approach and its implementation, we perform numerical experiments showing the steady propagation of single and the overtaking interaction of multiple BO solitary waves.
Oscillating flow of rarefied viscous gas between cylinders of finite length. Numerical study
Authors: Gospodinov P N , Dankov D Y , Mironova M K 
Published: December 2023

Abstract
The rarefied viscous gas flow between a stationary inner and an oscillating outer cylinder is studied in this paper. It is a continuation of our previous publications where we study the flow between the infinite length cylinders while here is considered the case of finite length cylinders bounded by two planes with periodic boundary conditions in the cross sections at the ends of the cylinders. So, on the one hand, this changes the flow character creating conditions for periodic self-organization along the axis of symmetry and on the other hand, the current model is reduced to a flow in a limited volume. A continuum model based on Navier-Stokes-Fourier equations for compressible fluid with first order slip boundary conditions on the cylinders wall and statistical model Direct Simulation Monte Carlo (DSMC) method are used to model the flow. The presented numerical results were obtained after reaching sustained oscillations. Considering the model with cylinders of finite length allows to extend its capabilities and obtain a better fit to real conditions.
Convergence of the L1 Two-Term Equation Scheme
Authors: Dimitrov Y. , Georgiev S. , Miryanov R. , Todorov V. 
Published: December 2023

Abstract
Fractional derivatives have found application in modeling various processes in different fields of science. Finite difference schemes are a main approach for numerical solution of models using fractional differential equations. In this paper we investigate the convergence and order of the numerical solution of two-term ordinary fractional differential equation which uses the L1 approximation of the fractional derivative. Inequalities for the weights of L1 approximation are derived and used to prove the convergence of the L1 scheme for the two-term equation. Conditions for the parameter of the two-term equation and error estimates of L1 scheme are obtained. Experimental results for the order and error of the L1 scheme are presented in the paper.
A structure-activity relationship modelling of opioid compounds by using machine learning
Authors: Sapundzhi Fatima , Lazarova Meglena , Dzimbova Tatyana , Georgiev Slavi , Ivanova Antonina 
Published: December 2023

Abstract
Opiates are among the oldest drugs that are used to treat many medical problems. They are analgesic and sedative drugs that contain opium. The morphine is its most active ingredient and it is a widely used pain reliever despite its side effects. The main objective of this study is to construct a model which gives the structure-activity relationship among a series of mu-opioid ligands and molecular docking results. For this purpose, a model of mu-opioid receptors using machine learning is introduced. By obtaining a relationship between the docking results and the in vivo test, we could predict the biological effect of the newly synthesized ligands.