bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanical properties of 2D Zr
n

+1C
n
(n = 1, 2) MXenes with and without functionalization
Authors: Li Hengtao , Wang Hongyan , Li Xiumei , Li Yong , Chen Yuanzheng , Wang Hui 
Published: September 2022

Abstract
Transition metal carbides and nitrides (MXenes) are considered the new generation of flexible electronic materials because of their superior mechanical strength and flexibility. Based on the density functional theory, the structures, electronic properties and mechanical properties of the 2D Zr-based MXenes with and without surface functional groups (O, F and OH) are investigated systematically to explore their elastic properties and tensile fracture mechanism. The results reveal the tensile strength and critical strain under biaxial tensile direction can reach 52 GPa, 12% for Zr2C and 55 GPa, 19% for Zr3C2, more outstanding than the mechanical behavior of the pristine Ti2C (47 GPa, 9.5%). The tensile behaviors of the functionalized Zr
n

+1CnT2 (n = 1, 2, T = O, F, OH) strongly depend on the crystallographic orientation and the surface functional group. The phonon spectrum under the critical strain indicates the tensile fracture of the pristine Zr-based MXenes was determined by phonon instability, except along the armchair direction of Zr2C and zigzag direction of Zr3C2. During tensile strain, the collapse of Zr
n

+1C
n
F2 and Zr
n

+1C
n
(OH)2 (n = 1, 2) are mainly caused by internal Zr–C bond rupture and transfer to the surface. While the O-functionalized Zr
n

+1C
n
O2 (n = 1, 2) presented the opposite collapse trend. Additionally, according to the research results of critical strain, elastic modulus and electrical conductivity, F/OH-terminated Zr2C MXene is relatively more suitable for flexible sensors of wearable devices than Zr3C2T2.
An educational review on distributed optic fiber sensing based on Rayleigh backscattering for damage tracking and structural health monitoring
Authors: Chamoin L , Farahbakhsh S , Poncelet M 
Published: September 2022

Abstract
This paper is a review on distributed optic fiber sensing for structural health monitoring applications, with a deeper focus on technologies relying on the Rayleigh backscattering phenomenon. It addresses the basic physical principles which are involved, the implementation and instrumentation of the measurement techniques, as well as recent practical applications, current performance, and remaining challenges. Being written at an elementary level and integrating relevant theoretical and technical details, we hope the document can be useful for researchers and engineers looking for an up-to-date overview on a field which currently undergoes significant development and increasing attractiveness, in particular for damage tracking in complex mechanical structures.
Black tea quality determination using a generic resistive gas sensor
Authors: Hosseini-Golgoo S M , Saeedi-Mirakmahaleh M , Saberi H 
Published: September 2022

Abstract
In this study, we present an analysis on the dynamic fermentation profile of a generic resistive gas sensor to optimize the process of turning green leaves into black tea and determine the quality of manufactured black tea, which are two crucial issues in the tea industry. The leaves were plucked from Lahijan and Rudsar, two important cultivation areas in Iran, in spring, summer and autumn. The results showed that the tea leaves optimum fermentation time (OFT) coincides with the second highest peak in the sensor’s dynamic fermentation profile. For example, various experiments showed that the second peak in the sensor’s dynamic response for the Lahijan summer tea samples, which had experienced optimal manufacturing stages, occurs in 117 ± 2 min. Also, tea tasters announced the OFT of 120 min for these samples by carefully examining five traits of the manufactured black tea. It was observed that the occurrence of this second peak is prolonged and even disappears as the quality of black tea decreases. To find the final black tea quality, we introduce a coordinate plane whose axes are determined based on the amplitude of the first peak and the occurrence of the second peak in the sensor’s dynamic fermentation profile. In this method, the characteristics of an optimal sample should be considered as a reference point. In the introduced classification space, the Euclidean distance of each point from the origin of the coordinates could also predict the tea taster’s score with a difference of ±0.5 marks. Finally, we show that the dynamic responses of a temperature-modulated gas sensor have sufficient discriminative features to segregate manufactured black tea samples based on their quality.
Multifunctional-high resolution imaging plate based on hydrophilic graphene for digital pathology
Authors: Lee Geonhee , Oh Yuna , Nam Jung Tae , Ji Seulgi , Jang A-Rang , Jeong Du Won , Kang MinSoung , Lee Sun Sook , Chae Soosang , Cho Donghwi , Hwang Jun Yeon , Lee Kyungeun , Lee Jeong-O 
Published: September 2022

Abstract
In the present study, we showed that hydrophilic graphene can serve as an ideal imaging plate for biological specimens. Graphene being a single-atom-thick semi-metal with low secondary electron emission, array tomography analysis of serial sections of biological specimens on a graphene substrate showed excellent image quality with improved z-axis resolution, without including any conductive surface coatings. However, the hydrophobic nature of graphene makes the placement of biological specimens difficult; graphene functionalized with polydimethylsiloxane oligomer was fabricated using a simple soft lithography technique and then processed with oxygen plasma to provide hydrophilic graphene with minimal damage to graphene. High-quality scanning electron microscopy images of biological specimens free from charging effects or distortion were obtained, and the optical transparency of graphene enabled fluorescence imaging of the specimen; high-resolution correlated electron and light microscopy analysis of the specimen became possible with the hydrophilic graphene plate.
OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines
Authors: Babier Aaron , Mahmood Rafid , Zhang Binghao , Alves Victor G L , Barragán-Montero Ana Maria , Beaudry Joel , Cardenas Carlos E , Chang Yankui , Chen Zijie , Chun Jaehee , Diaz Kelly , David Eraso Harold , Faustmann Erik , Gaj Sibaji , Gay Skylar , Gronberg Mary , Guo Bingqi , He Junjun , Heilemann Gerd , Hira Sanchit , Huang Yuliang , Ji Fuxin , Jiang Dashan , Carlo Jimenez Giraldo Jean , Lee Hoyeon , Lian Jun , Liu Shuolin , Liu Keng-Chi , Marrugo José , Miki Kentaro , Nakamura Kunio , Netherton Tucker , Nguyen Dan , Nourzadeh Hamidreza , Osman Alexander F I , Peng Zhao , Darío Quinto Muñoz José , Ramsl Christian , Joo Rhee Dong , David Rodriguez Juan , Shan Hongming , Siebers Jeffrey V , Soomro Mumtaz H , Sun Kay , Usuga Hoyos Andrés , Valderrama Carlos , Verbeek Rob , Wang Enpei , Willems Siri , Wu Qi , Xu Xuanang , Yang Sen , Yuan Lulin , Zhu Simeng , Zimmermann Lukas , Moore Kevin L , Purdie Thomas G , McNiven Andrea L , Chan Timothy C Y 
Published: September 2022

Abstract

Objective. To establish an open framework for developing plan optimization models for knowledge-based planning (KBP). Approach. Our framework includes radiotherapy treatment data (i.e. reference plans) for 100 patients with head-and-neck cancer who were treated with intensity-modulated radiotherapy. That data also includes high-quality dose predictions from 19 KBP models that were developed by different research groups using out-of-sample data during the OpenKBP Grand Challenge. The dose predictions were input to four fluence-based dose mimicking models to form 76 unique KBP pipelines that generated 7600 plans (76 pipelines × 100 patients). The predictions and KBP-generated plans were compared to the reference plans via: the dose score, which is the average mean absolute voxel-by-voxel difference in dose; the deviation in dose-volume histogram (DVH) points; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models. Main results. The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50–0.62, which indicates that the quality of the predictions was generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better (P < 0.05; one-sided Wilcoxon test) on 18 of 23 DVH points. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans, which satisfied 3.5% more criteria than the set of all dose predictions. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for an inverse planning model. Significance. This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. We found that the best performing models significantly outperformed the reference dose and dose predictions. In the interest of reproducibility, our data and code is freely available.
Automatic detection of primary and metastatic lesions on cervicothoracic region and whole-body bone using a uniform machine-learnable approach for [18F]-FDG-PET/CT image analysis
Authors: Nemoto Mitsutaka , Tanaka Atsuko , Kaida Hayato , Kimura Yuichi , Nagaoka Takashi , Yamada Takahiro , Hanaoka Kohei , Kitajima Kazuhiro , Tsuchitani Tatsuya , Ishii Kazunari 
Published: September 2022

Abstract
We propose a method to detect primary and metastatic lesions with Fluorine−18 fluorodeoxyglucose (FDG) accumulation in the lung field, neck, mediastinum, and bony regions on the FDG-PET/CT images. To search for systemic lesions, various anatomical structures must be considered. The proposed method is addressed by using an extraction process for anatomical regions and a uniform lesion detection approach. The uniform approach does not utilize processes that reflect any region-specific anatomical aspects but has a machine-learnable framework. Therefore, it can work as a lesion detection process for a specific anatomical region if it machine-learns the specific region data. In this study, three lesion detection processes for the whole-body bone region, lung field, or neck-mediastinum region are obtained. These detection processes include lesion candidate detection and false positive (FP) candidate elimination. The lesion candidate detection is based on a voxel anomaly detection with a one-class support vector machine. The FP candidate elimination is performed using an AdaBoost classifier ensemble. The image features used by the ensemble are selected sequentially during training and are optimal for candidate classification. Three-fold cross-validation was used to detect performance with the 54 diseased FDG-PET/CT images. The mean sensitivity for detecting primary and metastatic lesions at 3 FPs per case was 0.89 with a 0.10 standard deviation (SD) in the bone region, 0.80 with a 0.10 SD in the lung field, and 0.87 with a 0.10 SD in the neck region. The average areas under the ROC curve were 0.887 with a 0.125 SD for detecting bone metastases, 0.900 with a 0.063 SD for detecting pulmonary lesions, and 0.927 with a 0.035 SD for detecting the neck-mediastinum lesions. These detection performances indicate that the proposed method could be applied clinically. These results also show that the uniform approach has high versatility for providing various lesion detection processes.
XCIST—an open access x-ray/CT simulation toolkit
Authors: Wu Mingye , FitzGerald Paul , Zhang Jiayong , Segars W Paul , Yu Hengyong , Xu Yongshun , De Man Bruno 
Published: September 2022

Abstract

Objective. X-ray-based imaging modalities including mammography and computed tomography (CT) are widely used in cancer screening, diagnosis, staging, treatment planning, and therapy response monitoring. Over the past few decades, improvements to these modalities have resulted in substantially improved efficacy and efficiency, and substantially reduced radiation dose and cost. However, such improvements have evolved more slowly than would be ideal because lengthy preclinical and clinical evaluation is required. In many cases, new ideas cannot be evaluated due to the high cost of fabricating and testing prototypes. Wider availability of computer simulation tools could accelerate development of new imaging technologies. This paper introduces the development of a new open-access simulation environment for x-ray-based imaging. The main motivation of this work is to publicly distribute a fast but accurate ray-tracing x-ray and CT simulation tool along with realistic phantoms and 3D reconstruction capability, building on decades of developments in industry and academia. Approach. The x-ray-based Cancer Imaging Simulation Toolkit (XCIST) is developed in the context of cancer imaging, but can more broadly be applied. XCIST is physics-based, written in Python and C/C++, and currently consists of three major subsets: digital phantoms, the simulator itself (CatSim), and image reconstruction algorithms; planned future features include a fast dose-estimation tool and rigorous validation. To enable broad usage and to model and evaluate new technologies, XCIST is easily extendable by other researchers. To demonstrate XCIST’s ability to produce realistic images and to show the benefits of using XCIST for insight into the impact of separate physics effects on image quality, we present exemplary simulations by varying contributing factors such as noise and sampling. Main results. The capabilities and flexibility of XCIST are demonstrated, showing easy applicability to specific simulation problems. Geometric and x-ray attenuation accuracy are shown, as well as XCIST’s ability to model multiple scanner and protocol parameters, and to attribute fundamental image quality characteristics to specific parameters. Significance. This work represents an important first step toward the goal of creating an open-access platform for simulating existing and emerging x-ray-based imaging systems. While numerous simulation tools exist, we believe the combined XCIST toolset provides a unique advantage in terms of modeling capabilities versus ease of use and compute time. We publicly share this toolset to provide an environment for scientists to accelerate and improve the relevance of their research in x-ray and CT.
Adaptive margins for online adaptive radiotherapy
Authors: van der Bijl Erik , Remeijer Peter , Sonke Jan-Jakob , van der Heide Uulke A , Janssen Tomas 
Published: September 2022

Abstract

Objective. In online adaptive radiotherapy a new plan is generated every fraction based on the organ and clinical target volume (CTV) delineations of that fraction. This allows for a planning target volume margin that does not need to be constant over the whole course of treatment, as is the case in conventional radiotherapy. This work aims to introduce an approach to update the margins each fraction based on the per-patient treatment history and explore the potential benefits of such adaptive margins. Approach. We introduce a novel methodology to implement adaptive margins, isotropic and anisotropic, during a treatment course based on the accumulated dose to the CTV. We then simulate treatment histories for treatments delivered in up to 20 fractions using various choices for the standard deviations of the systematic and random errors and homogeneous and inhomogeneous dose distributions. The treatment-averaged adaptive margin was compared to standard constant margins. The change in the minimum dose delivered to the CTV was compared on a patient and a population level. All simulations were performed within the van Herk approach and its known limitations. Main results. The population mean treatment-averaged margins are down to 70% and 55% of the corresponding necessary constant margins for the isotropic and anisotropic approach. The reduction increases with longer fractionation schemes and an inhomogeneous target dose distribution. Most of the benefit can be attributed to the elimination of the effective systematic error over the course of treatment. Interpatient differences in treatment-averaged margins were largest for the isotropic margins. For the 10% of patients that would receive a lower than prescribed dose to the CTV this minimum dose to the CTV is increased using the adaptive margin approaches. Significance. Adaptive margins can allow to reduce margins in most patients without compromising patients with greater than average target motion.
Lamb wavefield-based monogenic signal processing for quantifying delamination in composite laminates
Authors: Sun Hu , Shao Weihan , Song Jiannan , Yang Xiaofeng , Wang Yishou , Qing Xinlin 
Published: September 2022

Abstract
Delamination is one of the common damages affecting the safety of composite structures. In this paper, a Lamb wavefield-based monogenic signal processing algorithm is proposed to quantify the delamination parameters in composite laminates, including location, size, shape, and depth. A quality-guided fast phase unwrapping algorithm is developed to solve the problem of phase wrapping after Riesz transform-based monogenic signal processing. Then, space distribution of the phase of Lamb wavefield can be extracted for calculating wavenumber distribution, which is related to the structural thickness or delamination depth and can be used for delamination imaging. Simulated Lamb wavefield signals calculated by finite element simulation are employed to evaluate the parameters of delamination in composite laminates. Compared with other traditional methods, the damage identification algorithm based on Riesz transform has excellent identification effect and shorter calculation time. The results show that the algorithm can be used not only for single delamination recognition but also for multi-delamination recognition with good accuracy. In particular, the interaction between incident waves along different ply directions and delamination is explored, and its influence on delamination quantification is studied, whose results are worthy of attention in engineering application. Finally, a completely non-contact laser ultrasonic system is established to obtain the Lamb wavefield with delamination. Experiments show that the algorithm can accurately quantify the location, size, shape, and depth of delamination.
Experimental evaluation of SMA-based multi-ring damping devices
Authors: Salehi Mohammad , Hodgson Darel , Parnell T Kim , DesRoches Reginald , Mild Edward 
Published: September 2022

Abstract
This paper investigates the performance of shape memory alloy (SMA)-based multi-ring (SBMR) damping devices through an extensive experimental program. SBMR devices were recently proposed for the seismic damage mitigation of building structures. These devices combine the shape recovery capability of austenitic NiTi rings with the high energy dissipation of a ring made of other metals, such as mild steel or martensitic NiTi, to achieve a balanced performance in terms of energy dissipation and self-centering. The experimental program consisted of two phases: (I) material testing, and (II) device testing. Phase I aimed at selecting the optimal heat treatments of austenitic and martensitic NiTi alloys for potential application in SBMR devices. To this end, 24 NiTi rod samples with various heat treatments were tested under uniaxial cyclic loading. With an optimal heat treatment, the residual strain of austenitic NiTi rods could be limited to less than 0.1% after 6% of elongation. In phase II, three rings made of austenitic NiTi, martensitic NiTi, and A36 steel, as well as a double-ring device and a triple-ring device, were tested under various bidirectional loading protocols. The test results showed that the austenitic NiTi ring with an optimized heat treatment could provide more than 93% of self-centering, but only less than 5% of effective damping ratio. However, both the double- and triple-ring devices provided at least 64% of self-centering and up to 16% of effective damping ratio. SBMR devices were also found capable of remaining usable after at least three strong seismic events with different durations.
Non-trivial band topology in the superconductor AuSn4: a first principle study
Authors: Karn N K , Sharma M M , Awana V P S 
Published: September 2022

Abstract
Topological semimetals such as Weyl or Dirac semimetal with superconductivity have emerged as a new class of topological materials to realize and study Majorana Fermion. This article reports the density functional theory calculated bulk electronic band structure of recently discovered topological superconductor candidate AuSn4. The study has been performed on AuSn4 considering two space groups symmetries viz. Aea2 and Ccce as reported earlier. This study is further extended to the calculation of Z2 invariants. The Fermi surfaces corresponding to the bands, which are responsible for non-trivial band topology along with the surface states are also mapped. The complete study suggests that AuSn4 is a topological semimetal. On AuSn4, it is the first report in the literature showing the non-trivial band topology based on first-principle calculations.
Electron correlations in the

Hc2

of Fe
y
Se

1−x

S
x
(0.10

⩽x⩽

0.24,

y⩾

0.9)
Authors: Wang Aifeng , Petrovic C 
Published: September 2022

Abstract
We report on the evolution of the electronic correlation strength across the nematic critical point in Fe
y
Se

1
−
x

S
x
(

0.10
⩽
x
⩽
0.24
;
y
⩾
0.9

), inferred from the measurements of the slope of the upper critical field

H

c
2

. Superconducting transition T

c
and quasiparticle mass

m
∗

exhibit similar reduction with sulfur content x. Our results indicate that electronic correlations from all Fermi surface pockets show strong interconnection with pairing strength and are not governed by the change of nematic fluctuations. The upper critical field anisotropy γ

H
=

H

c
2

a
b

/

H

c
2

c

exhibits a minimum in the critical region and stronger temperature dependence away from it.
Cosmological dependence of sterile neutrino dark matter with self-interacting neutrinos
Authors: Chichiri Carlos , Gelmini Graciela B. , Lu Philip , Takhistov Volodymyr 
Published: September 2022

Abstract
Unexplored interactions of neutrinos could be the key to understanding the nature of the dark matter (DM). In particular, active neutrinos with new self-interactions can produce keV-mass sterile neutrinos that account for the whole of the DM through the Dodelson-Widrow mechanism for a large range of active-sterile mixing values. This production typically occurs before Big-Bang Nucleosynthesis (BBN) in a yet uncharted era of the Universe.
We assess how the mixing range for keV-mass sterile neutrino DM is affected by the uncertainty in the early Universe pre-BBN cosmology.
This is particularly relevant for identifying the viable parameter space of sterile neutrino searches allowed by all astrophysical limits, as well as for cosmology, since the detection of a sterile neutrino could constitute the first observation of a particle providing information about the pre-BBN epoch. We find that the combined uncertainties in the early Universe cosmology and neutrino interactions significantly expand the allowed parameter space for sterile neutrinos that can constitute the whole of the DM.