bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wafer-scale controlled growth of MoS2 by magnetron sputtering: from in-plane to inter-connected vertically-aligned flakes
Authors: Wadhwa Riya , Thapa Sanjeev , Deswal Sonia , Kumar Pradeep , Kumar Mukesh 
Published: January 2023

Abstract
Recently, Molybdenum disulfide (MoS2) has attracted great attention due to its unique characteristics and potential applications in various fields. The advancements in the field have substantially improved at the laboratory scale however, a synthesis approach that produces large area growth of MoS2 on a wafer scale is the key requirement for the realization of commercial two-dimensional (2D) technology. Herein, we report tunable MoS2 growth with varied morphologies via radio frequency magnetron sputtering by controlling growth parameters. The controlled growth from in-plane to vertically-aligned (VA) MoS2 flakes has been achieved on a variety of substrates (Si, Si/SiO2, sapphire, quartz, and carbon fiber). Moreover, the growth of VA MoS2 is highly reproducible and is fabricated on a wafer scale. The flakes synthesized on the wafer show high uniformity, which is corroborated by the spatial mapping using Raman over the entire 2-inch Si/SiO2 wafer. The detailed morphological, structural, and spectroscopic analysis reveals the transition from in-plane MoS2 to VA MoS2 flakes. This work presents a facile approach to directly synthesize layered materials by sputtering technique on wafer scale. This paves the way for designing mass production of high-quality 2D materials, which will advance their practical applications by integration into device architectures in various fields.
Deep learning based direct segmentation assisted by deformable image registration for cone-beam CT based auto-segmentation for adaptive radiotherapy
Authors: Liang Xiao , Morgan Howard , Bai Ti , Dohopolski Michael , Nguyen Dan , Jiang Steve 
Published: January 2023

Abstract
Cone-beam CT (CBCT)-based online adaptive radiotherapy calls for accurate auto-segmentation to reduce the time cost for physicians. However, deep learning (DL)-based direct segmentation of CBCT images is a challenging task, mainly due to the poor image quality and lack of well-labelled large training datasets. Deformable image registration (DIR) is often used to propagate the manual contours on the planning CT (pCT) of the same patient to CBCT. In this work, we undertake solving the problems mentioned above with the assistance of DIR. Our method consists of three main components. First, we use deformed pCT contours derived from multiple DIR methods between pCT and CBCT as pseudo labels for initial training of the DL-based direct segmentation model. Second, we use deformed pCT contours from another DIR algorithm as influencer volumes to define the region of interest for DL-based direct segmentation. Third, the initially trained DL model is further fine-tuned using a smaller set of true labels. Nine patients are used for model evaluation. We found that DL-based direct segmentation on CBCT without influencer volumes has much poorer performance compared to DIR-based segmentation. However, adding deformed pCT contours as influencer volumes in the direct segmentation network dramatically improves segmentation performance, reaching the accuracy level of DIR-based segmentation. The DL model with influencer volumes can be further improved through fine-tuning using a smaller set of true labels, achieving mean Dice similarity coefficient of 0.86, Hausdorff distance at the 95th percentile of 2.34 mm, and average surface distance of 0.56 mm. A DL-based direct CBCT segmentation model can be improved to outperform DIR-based segmentation models by using deformed pCT contours as pseudo labels and influencer volumes for initial training, and by using a smaller set of true labels for model fine tuning.
Building an automated, machine learning-enabled platform for predicting post-operative complications
Authors: Balch Jeremy A , Ruppert Matthew M , Shickel Benjamin , Ozrazgat-Baslanti Tezcan , Tighe Patrick J , Efron Philip A , Upchurch Gilbert R , Rashidi Parisa , Bihorac Azra , Loftus Tyler J 
Published: January 2023

Abstract

Objective. In 2019, the University of Florida College of Medicine launched the MySurgeryRisk algorithm to predict eight major post-operative complications using automatically extracted data from the electronic health record. Approach. This project was developed in parallel with our Intelligent Critical Care Center and represents a culmination of efforts to build an efficient and accurate model for data processing and predictive analytics. Main Results and Significance. This paper discusses how our model was constructed and improved upon. We highlight the consolidation of the database, processing of fixed and time-series physiologic measurements, development and training of predictive models, and expansion of those models into different aspects of patient assessment and treatment. We end by discussing future directions of the model.
3D ECG display with deep learning approach for identification of cardiac abnormalities from a variable number of leads
Authors: Bortolan Giovanni 
Published: January 2023

Abstract

Objective. The objective of this study is to explore new imaging techniques with the use of the deep learning method for the identification of cardiac abnormalities present in electrocardiogram (ECG) signals with 2, 3, 4, 6 and 12-lead in the framework of the PhysioNet/Computing in Cardiology Challenge 2021. The training set is a public database of 88,253 twelve-lead ECG recordings lasting from 6 s to 60 s. Each ECG recording has one or more diagnostic labels. The six-lead, four-lead, three-lead, and two-lead are reduced-lead versions of the original twelve-lead data. Approach. The deep learning method considers images that are built from raw ECG signals. This technique considers innovative 3D display of the entire ECG signal, observing the regional constraints of the leads, obtaining time-spatial images of the 12 leads, where the x-axis is the temporal evolution of ECG signal, the y-axis is the spatial location of the leads, and the z-axis (color) the amplitude. These images are used for training Convolutional Neural Networks with GoogleNet for ECG diagnostic classification. Main results. The official results of the classification accuracy of our team named ‘Gio_new_img’ received scores of 0.4, 0.4, 0.39, 0.4 and 0.4 (ranked 18th, 18th, 18th,18th, 18th out of 39 teams) for the 12-lead, 6-lead, 4-lead, 3-lead, and 2-lead versions of the hidden test set with the Challenge evaluation metric. Significance. The results indicated that all these algorithms have similar behaviour in the various lead groups, and the most surprising and interesting point is the fact that the 2-lead scores are similar to those obtained with the analysis of 12 leads. It permitted to test the diagnostic potential of the reduced-lead ECG recordings. These aspects can be related to the pattern recognition capacity and generalizability of the deep learning approach and/or to the fact that the characteristics of the considered cardiac abnormalities can be extracted also from a reduced set of leads.
Impact of surface charges on energy deposition in surface dielectric barrier discharge: a modeling investigation
Authors: Ren Chenhua , Huang Bangdou , Zhang Cheng , Qi Bo , Chen Weijiang , Shao Tao 
Published: January 2023

Abstract
Surface charges have significant impact on the evolution of surface dielectric barrier discharge (SDBD). In this work, the role of residual surface charges on repetitively nanosecond pulsed SDBD in atmospheric air is investigated using a two-dimensional fluid model, based on the assumption of preserving the distribution of surface charges at the end of the previous high voltage (HV) pulse. In the bipolar mode when the polarity of residual surface charges is opposite to that of the current HV pulse, a lower breakdown voltage and more deposited energy can be observed, showing an obvious enhancement of SDBD. In the unipolar mode, residual surface charges suppress the development of discharges and energy deposition. It is found that more residual surface charges are accumulated during the negative pulsed discharge, which have a more pronounced effect on the subsequent positive pulsed one. This is explained by the fact that the negative surface streamers directly contact the dielectric and charge it, while the positive surface streamers float above the dielectric, forming a ion-rich region near the surface. The results in this work demonstrate the mechanism of how residual surface charges affect discharge dynamics, which can be utilized to regulate energy deposition in SDBDs.
Flexible skin for measurement of boundary layer state and flight attitude identification on UAV
Authors: Pang Peng , Zhao Keli , Zhong Siyuan , Luo Wei , Wei Jianfeng , He Kaifeng , Ma Binghe , Luo Jian , Deng Jinjun 
Published: January 2023

Abstract
The wall shear stress and pressure are important for analyzing boundary layer flow and evaluating the aerodynamic performance of the aircraft. In this study, a flexible skin consisting of dual layer hot-film sensors and pressure belts was developed to measure the distribution of wall shear stress and pressure on an unmanned aerial vehicle during increase of angle of attack (AOA), tail spin, and decreases of AOA. The sensitivity of the dual layer hot-film sensor is improved by about 150% due to heat conduction reduced. The relative error of pressure belt is less than 1% at 10 °C–65 °C. The boundary layer separation and reattachment time, separation AOA and time-shift of the flow field changes in flight conditions are determined. The separated AOA of the left and right wing boundary layers are 26.41° and 17.58° respectively. There is a delay about 4 s between the separation of the boundary layer and the entry of the tail spin, which can provide early warning to prevent abnormal flight conditions such as post stall and tail spin.
Enhanced conductance of molecular states at interstitial sites
Authors: Homberg Jan , Gruber Manuel , Weismann Alexander , Berndt Richard 
Published: January 2023

Abstract
Arrays of phthalocyanine molecules on Pb(100) are investigated with scanning tunneling microscopy. Maps of the differential conductance exhibit drastic changes as the sample voltage is being varied. Maximal conductances are observed at positions between the molecules mimicking bonding states. However, the maxima are shown to result from a superposition of non-interacting states. We expect that this effect may be observed from many other molecules.
Tailoring near-field-mediated photon electron interactions with light polarization
Authors: Chahshouri Fatemeh , Talebi Nahid 
Published: January 2023

Abstract
Inelastic interaction of free-electrons with optical near fields has recently attracted attention for manipulating and shaping free-electron wavepackets. Understanding the nature and the dependence of the inelastic cross section on the polarization of the optical near-field is important for both fundamental aspects and the development of new applications in quantum-sensitive measurements. Here, we investigate the effect of the polarization and the spatial profile of plasmonic near-field distributions on shaping free-electrons and controlling the energy transfer mechanisms, but also tailoring the electron recoil. We particularly show that polarization of the exciting light can be used as a control knop for disseminating the acceleration and deceleration path ways via the experienced electron recoil. We also demonstrate the possibility of tailoring the shape of the localized plasmons by incorporating specific arrangements of nanorods to enhance or hamper the transversal and longitudinal recoils of free-electrons. Our findings open up a route towards plasmonic near-fields-engineering for the coherent manipulation and control of slow electron beams for creating desired shapes of electron wavepackets.
Two-dimensional dual topological insulator in hexagonal IrO
Authors: Li W Q , Zhou P , Sun L Z 
Published: January 2023

Abstract
Double topological insulators (DTIs) are systems with two kinds of nontrivial topological indexes. Three-dimensional materials with dual-topological character (DTC) have received extensive research, whereas two-dimensional (2D) DTIs have received less attention. In this paper, we propose a new 2D DTI IrO material by using first-principles calculations. Further calculation reveal it is energetically, dynamically, and mechanically stable. There is a direct band gap in the electronic band structures with and without spin–orbit coupling (SOC), and a SOC-induced band inversion occurs at the M point. Based on the symmetry analysis and the
k
·
p
model, the topological invariant Z2 and mirror Chern number C

m
are determined to be nontrivial. The DTC is supported further by the different behavior of the edge states with and without the mirror symmetry breaking. Our theoretical prediction broadens the domain of candidate 2D DTIs in terms of topological manifestations as well as material realization.
Growth and temperature tuned band gap characteristics of NaBi(MoO4)2 single crystal
Authors: Isik M , Guler I , Gasanly N M 
Published: January 2023

Abstract
Structural and optical properties of double sodium–bismuth molybdate NaBi(MoO4)2 semiconductor compound was investigated by x-ray diffraction, Raman and transmission experiments. From the x-ray diffraction experiments, the crystal that has tetragonal structure was obtained. Vibrational modes of the crystal were found from the Raman experiments. Transmission experiments were performed in the temperature range of 10–300 K. Derivative spectroscopy analysis and absorption spectrum analysis were performed to get information about the change in band gap energy of the crystal with temperature. It was observed that the band gap energies of the crystal at different temperatures obtained from these techniques are well consisted with each other. By the help of absorption spectrum which was obtained from transmission measurements performed at varying temperatures, absolute zero value of the band gap and average phonon energy as 3.03 ± 0.02 eV and

E

p
h

= 24 ± 0.2 meV, respectively. Moreover, based on absorption spectrum analysis the Urbach energy of the crystal was obtained as 0.10 eV.
Greedy permanent magnet optimization
Authors: Kaptanoglu Alan A. , Conlin Rory , Landreman Matt 
Published: January 2023

Abstract
A number of scientific fields rely on placing permanent magnets in order to produce a desired magnetic field. We have shown in recent work that the placement process can be formulated as sparse regression. However, binary, grid-aligned solutions are desired for realistic engineering designs. We now show that the binary permanent magnet problem can be formulated as a quadratic program with quadratic equality constraints, the binary, grid-aligned problem is equivalent to the quadratic knapsack problem with multiple knapsack constraints, and the single-orientation-only problem is equivalent to the unconstrained quadratic binary problem. We then provide a set of simple greedy algorithms for solving variants of permanent magnet optimization, and demonstrate their capabilities by designing magnets for stellarator plasmas. The algorithms can a-priori produce sparse, grid-aligned, binary solutions. Despite its simple design and greedy nature, we provide an algorithm that compares with or even outperforms the state-of-the-art algorithms while being substantially faster, more flexible, and easier to use.
Dynamic investigations on hydrogen–helium interaction around the vacancy in BCC iron from ab-initio calculations
Authors: Luo Fengping , Huang Jia , Liu Qingyuan , Gao Zhiying , Ge Wei , Gao Fei , Wang Yugang , Wang Chenxu 
Published: January 2023

Abstract
Coexistence of hydrogen (H) and helium (He) under vacancy (V) supersaturation in the fusion environment alters the dynamic evolution of cavities and ultimately influences the swelling of structural materials. Herein, we investigate H–He interaction around a V as one prototype trapping site for H and He in body-centered cubic (BCC) iron (Fe) utilizing ab initio calculations from the thermal dynamics. First, we demonstrate the significantly stronger He–V interaction than H–V interaction by comparing the dynamic trapping and de-trapping of H with those of He. Furthermore, we confirm the repulsive H–He interaction around the V by examining their hopping around H–He–V complexes. The prior He in the V imposes weak influence on the dynamic trapping of H while enhances H de-trapping. Due to the prior He, more H atoms can be accommodated in the V resulting from larger H–H distances to attenuate repulsive H–H interaction. The dynamic trapping of He by the V is weakly influenced, even though the V is densely coated by the prior H. There exists a critical density of the prior H in the V, below which the prior H enhances He de-trapping. Above this critical density, He de-trapping is inhibited by the prior H. This work provides significant dynamic insights at the atomic scale toward a better understanding of the cavity nucleation and H isotopes/He retention in structural materials in the fusion environment.
Surface characterization and analysis of textured injection moulded PC-ABS automotive interior components
Authors: Reddy Vijeth V , Krishna Amogh V , Sjögren Anders , Rosén Bengt-Göran 
Published: January 2023

Abstract
Automotive interior components are produced by injection moulding due to its cost effectiveness in mass production. The surfaces of these components are textured to control the appearance and other surface functional properties such as wear and scratch resistance. Key challenges lie in replicating the features of mould tool with high aspect ratio which are influenced by the polymer and large number of process variables. Hence, to control the aesthetic properties, it is important to improve the understanding of the replication of textured surfaces and its relationship with measured gloss. In this study, the surface topography of PC-ABS samples is investigated using coherence scanning interferometry. Replication of two types- coarse and fine grain surface texture are investigated to identify the effects of tool temperature, injection speed and holding pressure. Areal surface parameters are scrutinized for the quantitative characterization and discrimination of study samples surface topographies. The correlations between process parameters, measured gloss and areal surface parameters are discussed. The results show significant influence of process variables on the replication of surface topography and measured gloss. The grain pattern governed the set of surface parameters selected and the variation in gloss. The process variables are observed to influence different region or distribution of specific surface features represented by surface parameters.
Variations in phenological, physiological, plant architectural and yield-related traits, their associations with grain yield and genetic basis
Authors: Li Yibo , Tao Fulu , Hao Yuanfeng , Tong Jingyang , Xiao Yonggui , He Zhonghu , Reynolds Matthew 
Published: January 2023

AbstractBackground and AimsPhysiological and morphological traits play essential roles in wheat (Triticum aestivum) growth and development. In particular, photosynthesis is a limitation to yield. Increasing photosynthesis in wheat has been identified as an important strategy to increase yield. However, the genotypic variations and the genomic regions governing morphological, architectural and photosynthesis traits remain unexplored.MethodsHere, we conducted a large-scale investigation of the phenological, physiological, plant architectural and yield-related traits, involving 32 traits for 166 wheat lines during 2018–2020 in four environments, and performed a genome-wide association study with wheat 90K and 660K single nucleotide polymorphism (SNP) arrays.Key ResultsThese traits exhibited considerable genotypic variations in the wheat diversity panel. Higher yield was associated with higher net photosynthetic rate (r = 0.41, P &lt; 0.01), thousand-grain weight (r = 0.36, P &lt; 0.01) and truncated and lanceolate shape, but shorter plant height (r = −0.63, P &lt; 0.01), flag leaf angle (r = −0.49, P &lt; 0.01) and spike number per square metre (r = −0.22, P &lt; 0.01). Genome-wide association mapping discovered 1236 significant stable loci detected in the four environments among the 32 traits using SNP markers. Trait values have a cumulative effect as the number of the favourable alleles increases, and significant progress has been made in determining phenotypic values and favourable alleles over the years. Eleven elite cultivars and 14 traits associated with grain yield per plot (GY) were identified as potential parental lines and as target traits to develop high-yielding cultivars.ConclusionsThis study provides new insights into the phenotypic and genetic elucidation of physiological and morphological traits in wheat and their associations with GY, paving the way for discovering their underlying gene control and for developing enhanced ideotypes in wheat breeding.
Evolution of hygrophytic plant species in the Anatolia–Caucasus region: insights from phylogenomic analyses ofCardamineperennials
Authors: Kantor Adam , Kučera Jaromír , Šlenker Marek , Breidy Joêlle , Dönmez Ali A , Marhold Karol , Slovák Marek , Svitok Marek , Zozomová-Lihová Judita 
Published: January 2023

AbstractBackground and AimsSouthwestern Asia is a significant centre of biodiversity and a cradle of diversification for many plant groups, especially xerophytic elements. In contrast, little is known about the evolution and diversification of its hygrophytic flora. To fill this gap, we focus on Cardamine (Brassicaceae) species that grow in wetlands over a wide altitudinal range. We aimed to elucidate their evolution, assess the extent of presumed historical gene flow between species, and draw inferences about intraspecific structure.MethodsWe applied the phylogenomic Hyb-Seq approach, ecological niche analyses and multivariate morphometrics to a total of 85 Cardamine populations from the target region of Anatolia–Caucasus, usually treated as four to six species, and supplemented them with close relatives from Europe.Key ResultsFive diploids are recognized in the focus area, three of which occur in regions adjacent to the Black and/or Caspian Sea (C. penzesii, C. tenera, C. lazica), one species widely distributed from the Caucasus to Lebanon and Iran (C. uliginosa), and one western Anatolian entity (provisionally C. cf. uliginosa). Phylogenomic data suggest recent speciation during the Pleistocene, likely driven by both geographic separation (allopatry) and ecological divergence. With the exception of a single hybrid (allotetraploid) speciation event proven for C. wiedemanniana, an endemic of southern Turkey, no significant traces of past or present interspecific gene flow were observed. Genetic variation within the studied species is spatially structured, suggesting reduced gene flow due to geographic and ecological barriers, but also glacial survival in different refugia.ConclusionsThis study highlights the importance of the refugial regions of the Black and Caspian Seas for both harbouring and generating hygrophytic species diversity in Southwestern Asia. It also supports the significance of evolutionary links between Anatolia and the Balkan Peninsula. Reticulation and polyploidization played a minor evolutionary role here in contrast to the European relatives.
The role of xanthine dioxygenase in the biosynthetic pathway of 2-aza-8-oxohypoxanthine ofLepista sordida
Authors: Kotajima Mihaya , Choi Jae-Hoon , Suzuki Tomohiro , Wu Jing , Hirai Hirofumi , Nelson David C , Ouchi Hitoshi , Inai Makoto , Dohra Hideo , Kawagishi Hirokazu 
Published: January 2023

ABSTRACT2-Azahypoxanthine (AHX) and 2-aza-8-oxohypoxanthine (AOH), discovered as causal substances of fairy rings are known to be endogenous in the fairy ring-forming Lepista sordida. In this study, we showed that xanthine dioxygenase, an a-ketoglutarate-dependent dioxygenase, might catalyze the conversion of AHX to AOH in the fungus. Furthermore, this enzyme is the first reported molybdopterin-independent protein of hypoxanthine metabolism.