bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementation of an interactive virtual microscope laboratory system in teaching oral histopathology
Authors: Qing Jia , Cheng Gu , Ni Xiao-Qi , Yang Yi , Zhang Wei , Li Zhi 
Published: March 2022

AbstractLaboratory course acts as a key component of histopathology education. Recent trends of incorporating visual and interactive technology in active and inquiry-based learning pedagogical methods have led to significant improvement of histopathology laboratory courses. The present work aimed to describe interactive virtual microscope laboratory system (IVMLS) as a virtual platform for teaching histopathology in order to improve the quality and efficiency of teaching. The system is based on interactive technology and consists of interactive software, slide-reading software, teaching resources and integrated auxiliary equipment. It allows real-time interaction between teachers and students and provides students with a wealth of learning and review materials. In order to evaluate the effectiveness of the system, we conducted a comparative study with the use of light microscope (LM) as a method. Specifically, we compared the results of six assignments and one laboratory final exam between IVMLS group and LM group to analyse the impact of IVMLS on students' academic performance. A questionnaire survey was also conducted to obtain students' attitudes and views on this system. There was no overall difference in assignment performance between IVMLS group and LM group. But laboratory final test grades increased from a mean of 62% (43.8–80.0, 95% CI) before to 83% (71.0–94.2, 95% CI) after implement IVMLS, suggesting highly significant (p < 0.001) improvement on students' histopathology laboratory performance. Feedback of the questionnaire was positive, indicating that students were satisfied with the system, which they believed improved student communication and teacher-student interaction, increased learning resources, increased their focus on learning, and facilitated their independent thinking process. This study proves that IVMLS is an efficient and feasible teaching technology and improves students' academic performance.
Machine learning to predict effective reaction rates in 3D porous media from pore structural features
Authors: Liu Min , Kwon Beomjin , Kang Peter K. 
Published: March 2022

AbstractLarge discrepancies between well-mixed reaction rates and effective reactions rates estimated under fluid flow conditions have been a major issue for predicting reactive transport in porous media systems. In this study, we introduce a framework that accurately predicts effective reaction rates directly from pore structural features by combining 3D pore-scale numerical simulations with machine learning (ML). We first perform pore-scale reactive transport simulations with fluid–solid reactions in hundreds of porous media and calculate effective reaction rates from pore-scale concentration fields. We then train a Random Forests model with 11 pore structural features and effective reaction rates to quantify the importance of structural features in determining effective reaction rates. Based on the importance information, we train artificial neural networks with varying number of features and demonstrate that effective reaction rates can be accurately predicted with only three pore structural features, which are specific surface, pore sphericity, and coordination number. Finally, global sensitivity analyses using the ML model elucidates how the three structural features affect effective reaction rates. The proposed framework enables accurate predictions of effective reaction rates directly from a few measurable pore structural features, and the framework is readily applicable to a wide range of applications involving porous media flows.
Dynamic analysis of QTLs on plant height with single segment substitution lines in rice
Authors: Fu Yu , Zhao Hongyuan , Huang Jiongkai , Zhu Haitao , Luan Xin , Bu Suhong , Liu Zupei , Wang Xiaoling , Peng Zhiqin , Meng Lijun , Liu Guifu , Zhang Guiquan , Wang Shaokui 
Published: March 2022

AbstractDynamic regulation of QTLs remains mysterious. Single segment substitution lines (SSSLs) and conditional QTL mapping and functional QTL mappings are ideal materials and methods to explore dynamics of QTLs for complex traits. This paper analyzed the dynamics of QTLs on plant height with SSSLs in rice. Five SSSLs were verified with plant height QTLs first. All five QTLs had significant positive effects at one or more developmental stages except QTL1. They interacted each other, with negative effects before 49 d after transplanting and positive effects since then. The five QTLs selectively expressed in specific periods, mainly in the periods from 35 to 42 d and from 49 to 56 d after transplanting. Expressions of epistasis were dispersedly in various periods, negative effects appearing mainly before 35 d. The five QTLs brought the inflexion point ahead of schedule, accelerated growth and degradation, and changed the peak plant height, while their interactions had the opposite effects. The information will be helpful to understand the genetic mechanism for developmental traits.
Temporal patterns of chronic disease incidence after breast cancer: a nationwide population-based cohort study
Authors: Kang Danbee , Kang Minwoong , Hong Yun Soo , Park Jihwan , Lee Jin , Seo Hwa Jeong , Kim Dong Wook , Ahn Jin Seok , Park Yeon Hee , Lee Se Kyung , Shin Dong Wook , Guallar Eliseo , Cho Juhee 
Published: March 2022

AbstractWe conducted a retrospective cohort study to evaluate the temporal pattern of incidence of chronic conditions after developing breast cancer using a population-based national registry. We selected 84,969 women with newly diagnosed breast cancer between 2002 and 2016 and a 1:10 sample of age-matched non-breast cancer controls (N = 1,057,674). The main study exposure was incident breast cancer, considered as a time-varying exposure. The outcomes were incident cases of leukemia, endometrial cancer, myeloma, cardiomyopathy, osteoporosis, end stage renal disease (ESRD), pulmonary fibrosis, hypothyroidism, type 2 diabetes, hypertension and hyperlipidemia. The development of breast cancer was associated with a significantly increased risk of all outcomes analyzed except for ESRD and hypertension. The fully-adjusted risks of leukemia (HR 3.09; 95% CI 2.11–4.51), cardiomyopathy (HR 2.65; 95% CI 1.90–3.68), endometrial cancer (HR 3.53; 95% CI 2.76–4.53), hypothyroidism (HR 1.29; 95% CI 1.19–1.40), pulmonary fibrosis (HR 1.84; 95% CI 1.12–3.02), and hyperlipidemia (HR 1.24; 95% CI 1.20–1.28) remained significantly elevated after more than 5 years since diagnosis. Optimal care for breast cancer survivors requires close collaboration between oncologists and allied health care professionals to identify and manage the long-term morbidity and mortality associated with these chronic conditions.
Disease progression patterns and molecular resistance mechanisms to crizotinib of lung adenocarcinoma harboring ROS1 rearrangements
Authors: Zhang Yongchang , Huang Zhe , Zeng Liang , Zhang Xiangyu , Li Yizhi , Xu Qinqin , Yang Haiyan , Lizaso Analyn , Xu Chunwei , Liu Jun , Wang Wenxian , Song Zhengbo , Ou Sai-Hong Ignatius , Yang Nong 
Published: March 2022

AbstractThis retrospective study investigated the association between the pattern of disease progression and molecular mechanism of acquired resistance in a large cohort of 49 patients with ROS1-rearranged advanced non-small-cell lung cancer treated with first-line crizotinib. We found that treatment-emergent ROS1 point mutations were the major molecular mechanism of crizotinib resistance, particularly for patients who developed extracranial-only disease progression. Our findings highlight the importance of rebiopsy and gene testing for subsequent-line therapeutic management.
Biomimetic multifunctional nanozymes enhanced radiosensitization for breast cancer via an X-ray triggered cascade reaction
Authors: Yang Lin , Du Xiao , Qin Yanru , Wang Xueyuan , Zhang Liefeng , Chen Zhimeng , Wang Zhongjie , Yang Xu , Lei Meng , Zhu Yongqiang 
Published: March 2022

Design and manufacture of an ultra-small bionic multifunctional nanozyme BSA@CNP/Fe2+ as a radiosensitizer to treat breast cancer.
Self‐attention mechanism for distributed compressive sensing
Authors: Shu Feng , Zhang Linghua , Ding Yin , Cheng Qin , Wang Xu 
Published: March 2022

AbstractThis letter addresses the joint sparse recovery problem with multiple measurement vectors in compressive sensing (CS). In this letter, it is assumed that the sparse vectors are related to each other but the specific dependencies are unknown. The authors propose a data‐driven approach that relies on a self‐attention mechanism to learn the sparse structure within and between sparse vectors automatically. A greedy method is then used to reconstruct the sparse vectors. The numerical experiments conducted on two real‐world datasets show that the proposed method outperforms the model‐based Bayesian methods and data‐driven method based on long short‐term memory.
Dependence of the vertical‐tunnel‐junction GaAs solar cell on concentration and temperature
Authors: Outes Celia , Fernández Eduardo F. , Seoane Natalia , Almonacid Florencia , García‐Loureiro Antonio J. 
Published: March 2022

AbstractModelling the current–voltage (I–V) characteristics of photovoltaic (PV) devices is important for understanding their behaviour and potential. Typically, the single exponential model (SEM) is used because of its simplicity and accuracy. In this work, we validate the SEM for a gallium arsenide (GaAs) vertical‐tunnel‐junction (VTJ) using TCAD software. This cell is the key to overcoming the series resistance limitations of current concentrator solar cells, which can lead to the development of ultra‐high concentrator photovoltaic systems (UHCPV) with concentrations (Cratio) greater than 1000 suns. The results indicate that the SEM is a suitable tool to model the I–V characteristics of the VTJ cell with mean errors lower than 1%. Moreover, the solar cell did not show any limitations regarding the Cratio and temperatures under investigation. In addition, the analysis of the temperature coefficients of the cell demonstrates that their dependency on temperature reduces as Cratio increases. The results of this work suggest that VTJ is a promising solution to produce a new generation of high‐efficiency and low‐cost UHCPV systems.
Theoretical analysis of surface brightness-colour relations for late-type stars using MARCS model atmospheres
Authors: Salsi A. , Nardetto N. , Plez B. , Mourard D. 
Published: March 2022

Context. Surface brightness-colour relations (SBCRs) are largely used for general studies in stellar astrophysics and for determining extragalactic distances. Based on a careful selection of stars and a homogeneous methodology, it has been recently shown that the SBCR for late-type stars depends on the spectral type and luminosity class.
Aims. Based on simulated spectra of late-type stars using MARCS model atmospheres, our aim is to analyse the effect of stellar fundamental parameters on the surface brightness. We also compare theoretical and recent empirical SBCRs.
Methods. We used MARCS model atmospheres to compute spectra and obtain the surface brightness of stars. We first explored the parameter space of MARCS (i.e. effective temperature, log g, [Fe/H], microturbulence, and mass) in order to quantify their impact on the surface brightness. Then we considered a relation between the effective temperature and log g for late dwarfs and giants, as well as a solar metallicity, in order to allow a consistent comparison of theoretical and empirical SBCRs.
Results. We find that the SBCR is not sensitive to the microturbulence and mass. The effect of metallicity on the SBCR is found to be larger for dwarfs than for giants. It is also larger when considering larger V - Ks values. We also find that a difference of 0.5 dex in metallicity between Galactic and LMC SBCRs does not affect the recent LMC distance determination, based on eclipsing binaries, by more than 0.4%. By comparing theoretical with empirical SBCRs, we find a good agreement of less than 2σ for F5-K7 dwarfs and giants stars, while a larger discrepancy is found for M dwarfs and giants (about 4-6σ). The surface gravity properties, as modelled in MARCS, explain the differences in the empirical SBCRs in terms of class. We finally find that theoretical and empirical SBCRs for Cepheids are consistent.
Conclusions. Carefully considering metallicity and log g is mandatory when calibrating or using SBCRs.
Luminosity selection for gamma-ray bursts
Authors: Banerjee S. , Guetta D. 
Published: March 2022

Aims.There exists inevitable scatter in the intrinsic luminosity of gamma-ray bursts (GRBs). If there is relativistic beaming in the source, viewing angle variation necessarily introduces variation in the intrinsic luminosity function (ILF). Scatter in the ILF can cause selection bias where sources detected at distance have a greater median luminosity than those detected close by. Median luminosity divides any given population into equal halves. When the functional form of a distribution is unknown, it can be a more robust diagnostic than those that use trial functional forms.Method.In this work, we employ a statistical test based on median luminosity and use it to test a class of models for GRBs. We assume that the GRB jet has a finite opening angle and that the orientation of the GRB jet is random relative to the observer. We calculateLmedianas a function of redshift by simulating GRBs empirically and theoretically, and use the luminosity-vs.-redshiftSwiftdata in order to compare the theoretical results with the observed ones. The method accounts for the fact that there may be GRBs that go undetected at some redshifts.Results.We find thatLmedianis extremely insensitive to the on-axis (i.e., maximal) luminosity of the jet.
Rate of pancreatic cancer following a negative endoscopic ultrasound and associated factors
Authors: King Dominic , Kamran Umair , Dosanjh Amandeep , Coupland Ben , Mytton Jemma , Leeds John S. , Nayar Manu , Patel Prashant , Oppong Kofi W. , Trudgill Nigel J. 
Published: March 2022

Background Data are limited regarding pancreatic cancer diagnosed following a pancreaticobiliary endoscopic ultrasound (EUS) that does not diagnose pancreatic cancer. We have studied the frequency of, and factors associated with, post-EUS pancreatic cancer (PEPC) and 1-year mortality.
Methods Between 2010 and 2017, patients with pancreatic cancer and a preceding pancreaticobiliary EUS were identified in a national cohort using Hospital Episode Statistics. Patients with a pancreaticobiliary EUS 6–18 months before a later pancreatic cancer diagnosis were the PEPC cases; controls were those with pancreatic cancer diagnosed within 6 months of pancreaticobiliary EUS. Multivariable logistic regression models examined the factors associated with PEPC and a Cox regression model examined factors associated with 1-year cumulative mortality.
Results 9363 pancreatic cancer patients were studied; 93.5 % identified as controls (men 53.2 %; median age 68 [interquartile range (IQR) 61–75]); 6.5 % as PEPC cases (men 58.2 %; median age 69 [IQR 61–77]). PEPC was associated with older age (≥ 75 years compared with < 65 years, odds ratio [OR] 1.42, 95 %CI 1.15–1.76), increasing co-morbidity (Charlson co-morbidity score > 5, OR 1.90, 95 %CI 1.49–2.43), chronic pancreatitis (OR 3.13, 95 %CI 2.50–3.92), and diabetes mellitus (OR 1.58, 95 %CI 1.31–1.90). Metal biliary stents (OR 0.57, 95 %CI 0.38–0.86) and EUS-FNA (OR 0.49, 95 %CI 0.41–0.58) were inversely associated with PEPC. PEPC was associated with a higher cumulative mortality at 1 year (hazard ratio 1.12, 95 %CI 1.02–1.24), with only 14 % of PEPC patients (95 %CI 12 %–17 %) having a surgical resection, compared with 21 % (95 %CI 20 %–22 %) of controls.
Conclusions PEPC occurred in 6.5 % of patients and was associated with chronic pancreatitis, older age, more co-morbidities, and specifically diabetes mellitus. PEPC was associated with a worse prognosis and lower surgical resection rates.
Pluto near the edge of chaos
Authors: Malhotra Renu , Ito Takashi 
Published: March 2022

Significance
The dwarf planet, Pluto, has stirred the imagination of the public and of planetary scientists due to its many unusual properties. Among these properties is its Neptune-crossing orbit whose stability is owed to an orbital resonance with Neptune. Less well understood is the role of the other planets. We demonstrate that the orbital architecture of the giant planets lies within a narrow niche in which Pluto-like orbits are practically stable on gigayear timescales, whereas nearby are strongly chaotic orbits. Pluto is witness to the dynamical history of the solar system; quantifying its proximity to strong chaos and dynamical instability can enable quantitative constraints on its own dynamical history as well as that of the solar system.
Discourse-driven asymmetries between embedded interrogatives and relative clauses in West Germanic
Authors: Bacskai-Atkari Julia 
Published: March 2022

Abstract
The article examines embedded constituent questions and relative clauses in West Germanic, arguing that asymmetries regarding doubly filled COMP patterns are due to information-structural differences. While both clause types involve operator movement, they differ crucially regarding the information-structural status of the operator: in interrogatives, the operator can be associated with discourse-new information, while in relative clauses the operator is discourse-old and can be potentially left out. This asymmetry regarding information-structural properties has further important consequences. First, doubling patterns involving an overt operator and an overt complementiser emerge across West Germanic languages in embedded questions but not in relative clauses. Second, the reanalysis of the operator into a complementiser is attested in relative clauses but not in embedded interrogatives.
Vector-valued spline method for the spherical multiple-shell electro-magnetoencephalography problem
Authors: Leweke S , Hauk O , Michel V 
Published: March 2022

Abstract
Human brain activity is based on electrochemical processes, which can only be measured invasively. Thus, quantities such as magnetic flux density (MEG) or electric potential differences (EEG) are measured non-invasively in medicine and research. The reconstruction of the neuronal current from the measurements is a severely ill-posed problem though the visualization of the cerebral activity is one of the main research tools in cognitive neuroscience. Here, using an isotropic multiple-shell model for the human head and a quasi-static approach for the electro-magnetic processes, we derive a novel vector-valued spline method based on reproducing kernel Hilbert spaces in order to reconstruct the current from the measurements. The presented method follows the path of former spline approaches and provides classical minimum norm properties. Besides, it minimizes the (infinite-dimensional) Tikhonov–Philips functional which handles the instability of the inverse problem. This optimization problem reduces to solving a finite-dimensional system of linear equations without loss of information, due to its construction. It results in a unique solution which takes into account that only the harmonic and solenoidal component of the neuronal current affects the measurements. Furthermore, we prove a convergence result: the solution achieved by the novel method converges to the generator of the data as the number of measurements increases. The vector splines are applied to the inversion of three synthetic test cases, where the irregularly distributed data situation could be handled very well. Combined with five parameter choice methods, numerical results are shown for synthetic test cases with and without additional Gaussian white noise. Former approaches based on scalar splines are outperformed by the novel vector splines results with respect to the normalized root mean square error. Finally, results for real data acquired during a visual stimulation task are demonstrated. They can be computed quickly and are reasonable with respect to physiological expectations.
Thin film block copolymer self-assembly for nanophotonics
Authors: Kulkarni Ashish A , Doerk Gregory S 
Published: March 2022

Abstract
The nanophotonic engineering of light–matter interactions has profoundly changed research behind the design and fabrication of optical materials and devices. Metasurfaces—arrays of subwavelength nanostructures that interact resonantly with electromagnetic radiation—have emerged as an integral nanophotonic platform for a new generation of ultrathin lenses, displays, polarizers and other devices. Their success hinges on advances in lithography and nanofabrication in recent decades. While existing nanolithography techniques are suitable for basic research and prototyping, issues of cost, throughput, scalability, and substrate compatibility may preclude their use for many metasurface applications. Patterning via spontaneous self-assembly of block copolymer thin films offers an enticing alternative for nanophotonic manufacturing that is rapid, inexpensive, and applicable to large areas and diverse substrates. This review discusses the advantages and disadvantages of block copolymer-based nanopatterning and highlights recent progress in their use for broadband antireflection, surface enhanced Raman spectroscopy, and other nanophotonic applications. Recent advances in diversification of self-assembled block copolymer nanopatterns and improved processes for enhanced scalability of self-assembled nanopatterning using block copolymers are also discussed, with a spotlight on directions for future research that would enable a wider array of nanophotonic applications.
Reverberation clutter signal suppression in ultrasound attenuation estimation using wavelet-based robust principal component analysis
Authors: Lok U-Wai , Gong Ping , Huang Chengwu , Tang Shanshan , Zhou Chenyun , Yang Lulu , Watt Kymberly D , Callstrom Matthew , Trzasko Joshua D , Chen Shigao 
Published: March 2022

Abstract

Objective. Ultrasound attenuation coefficient estimation (ACE) has diagnostic potential for clinical applications such as quantifying fat content in the liver. Previously, we have proposed a system-independent ACE technique based on spectral normalization of different frequencies, called the reference frequency method (RFM). This technique does not require a well-calibrated reference phantom for normalization. However, this method may be vulnerable to severe reverberation clutter introduced by the body wall. The clutter superimposed on liver echoes may bias the estimation. Approach. We proposed to use robust principal component analysis, combined with wavelet-based sparsity promotion, to suppress the severe reverberation clutters. The capability to mitigate the reverberation clutters was validated through phantom and in vivo studies. Main Results. In the phantom studies with added reverberation clutters, higher normalized cross-correlation and smaller mean absolute errors were attained as compared to RFM results without the proposed method, demonstrating the capability to reconstruct tissue signals from reverberations. In a pilot patient study, the correlation between ACE and proton density fat fraction (PDFF), a measurement of liver fat by MRI as a reference standard, was investigated. The proposed method showed an improvement of the correlation (coefficient of determination, R = 0.82) as compared with the counterpart without the proposed method (R = 0.69). Significance: The proposed method showed the feasibility of suppressing the reverberation clutters, providing an important basis for the development of a robust ACE with large reverberation clutters.