bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using small angle x-ray scattering to examine the aggregation mechanism in silica nanoparticle-based ambigels for improved optical clarity
Authors: Kashanchi Glareh N. , King Sophia C. , Ju Susan E. , Dashti Ali , Martinez Ricardo , Lin Yu-Keng , Wall Vivian , McNeil Patricia E. , Marszewski Michal , Pilon Laurent , Tolbert Sarah H. 
Published: December 2022

Silica-based aerogels are a promising low-cost solution for improving the insulation efficiency of single-pane windows and reducing the energy consumption required for space heating and cooling. Two key material properties required are high porosity and small pore sizes, which lead to low thermal conductivity and high optical transparency, respectively. However, porosity and pore size are generally directly linked, where high porosity materials also have large pore sizes. This is unfavorable as large pores scatter light, resulting in reduced transmittance in the visible regime. In this work, we utilized preformed silica colloids to explore methods for reducing pore size while maintaining high porosity. The use of preformed colloids allows us to isolate the effect of solution conditions on porous gel network formation by eliminating simultaneous nanoparticle growth and aggregation found when using typical sol–gel molecular-based silica precursors. Specifically, we used in situ synchrotron-based small-angle x-ray scattering during gel formation to better understand how pH, concentration, and colloid size affect particle aggregation and pore structure. Ex situ characterization of dried gels demonstrates that peak pore widths can be reduced from 15 to 13 nm, accompanied by a narrowing of the overall pore size distribution, while maintaining porosities of 70%–80%. Optical transparency is found to increase with decreasing pore sizes while low thermal conductivities ranging from 95 +/− 13 mW/m K are maintained. Mechanical performance was found to depend primarily on effective density and did not show a significant dependence on solution conditions. Overall, our results provide insights into methods to preserve high porosity in nanoparticle-based aerogels while improving optical transparency.
Photothermal effects on optical bistability and second-order sidebands in a cavity
Authors: Lv Jiang , Bi Jie , Xu Yifan , Li Tieping , Chen Hongyun 
Published: December 2022

Abstract
We theoretically study the optical bistability and second-order sideband generation (SSG) in an optical cavity having photothermal effect in our paper. Using the perturbation method, we give an explicit analytical expression for SSG, showing a conversion efficiency of over 30

%

. With change in the system parameters, our numerical method shows that the transparency window of the photothermal induced transparency and the SSG can be significantly enhanced by the photothermal effects. Our obtained results in this study can provide a reference to develop a new way in all-optical switching and precision measurement.
Backward scattering impact on the photoionization time delay of asymmetric molecules
Authors: Chen Xi , Cao Wei , Zhan BiFu , Lu Peixiang 
Published: December 2022

Abstract
The time delays in photoionization of asymmetric diatomic molecules are numerically investigated using the technique of reconstruction of attosecond beating by interference of two-photon transitions (RABBITTs). Our results show that two different oscillatory structures appear in the molecular photoionization time delays as the photoelectron energy changes, and the contribution of these two oscillations to the time delays varies with the nuclear distance. By using an analytical interference model, we demonstrate that one oscillation is traced back to the two-center interference and the other originates from the photoelectrons backward scattering. With the increases of internuclear distance, the backward scattering impact on the time delays is gradually distinct in a particular direction of the photoionization. The amplitude of the backward scattering induced oscillation decreases when the photoelectron energy increases. Furthermore, the stereo RABBITT time delays display a distinct downshift as the increases of asymmetry degree of molecule, which is attributed to the increasing depth of the additional Coulomb potential experienced by the ionized electron.
Multispectral tunable symmetry-protected bound states in the continuum in all-dielectric split-ring resonator metasurfaces
Authors: Sharma Shubhanshi , Lahiri Basudev , Varshney Shailendra 
Published: December 2022

Abstract
Symmetry incompatible bound states in the continuum (BICs) are the non-radiating states that remain decoupled from the radiation continuum due to the symmetry mismatch. However, it has always been challenging to observe multiple symmetry-protected BICs in single resonator dielectric metasurfaces. This work reports multiple symmetry-protected BICs for both linear polarizations in all-dielectric metasurfaces made up of split-ring resonators (SRRs). Intensive numerical simulations predict that SRR can support a high-quality factor (Q) of 106 for standalone and with substrate in presence of asymmetry. However, for a realistic and practical scenario, a Q-factor of

≈

8000 for standalone structures is achieved, which reduces by a factor of 1.25 in the presence of silica substrate. Even if the out-of-plane asymmetry is introduced either in the geometry or variation in the angle of incidence, BICs are transformed into quasi-BICs possessing Fano resonance. Eigenmode and multipole decomposition analysis confirm multiple BIC resonances; notable dominant contributions are from magnetic dipole, toroidal dipole, and electric and magnetic quadrupoles. Integrating monolayer graphene adds tunability to the metasurface, where distinct quasi-BIC modes can be employed to facilitate an excellent switching.
Investigation of deep transfer learning for cross-turbine diagnosis of wind turbine faults
Authors: Xie Ping , Zhang Xingmin , Jiang Guoqian , Cui Jian , He Qun 
Published: December 2022

Abstract
Data-driven fault diagnosis of wind turbines has gained popularity, and various deep learning models have been developed accordingly with massive amounts of data and achieved an excellent diagnosis performance. However, most existing deep learning models require a similar distribution of both training and testing data, thus the trained model cannot generalize new wind turbines with different data distributions. In addition, there are insufficient fault data in practice, and therefore the cost of training a new model from scratch is extremely high. To solve these problems, a cross-turbine fault diagnosis method based on deep transfer learning is proposed for wind turbines with the available supervisory control and data acquisition (SCADA) data. To better capture the spatial features of SCADA data, a deep multi-scale residual attention convolutional neural network (DMRACNN) is first designed. Then, the distribution differences between the source and target domain data are aligned at feature level. Specifically, we investigate the transfer performance of four different domain adaptation metrics. We evaluate our proposed method using SCADA data from two wind turbines to compare the diagnostic performance of four basic networks combined with four transfer metrics. Compared with traditional deep learning methods, our proposed DMRACNN achieved significant performance improvements. A cross-validation experiment using two turbines demonstrates the strong generalization ability of the proposed method.
Analysis of uncertainties in the measurement of the space charge distribution in dielectrics
Authors: Pan Jiaping , Cao Zebin , Zheng Feihu , Zhang Yewen 
Published: December 2022

Abstract
The results obtained from the commonly used space charge distribution measurement methods are frequently apparent and one-dimensional results of a localized area; moreover, random errors can be caused by various factors. In this work, three factors—sample thickness uniformity, pressure wave intensity uniformity, and space charge distribution uniformity—that may cause measurement uncertainties are examined. The analysis and evaluation of the experimental data are affected by the measurement uncertainties, which are particularly noticeable in experiments on semiconductive electrode-flat polyethylene samples that use the laser-induced pressure propagation method. These factors are investigated separately using several auxiliary experiments, including laser beam spot energy distribution measurements and space charge distribution measurements, at different measurement positions on the same uniform sample. A clear and intelligible model is developed to discuss the influence of these factors on the uncertainties in the space charge distribution measurement in dielectrics.
Minimizing susceptibility-induced BOLD sensitivity loss in multi-band accelerated fMRI using point spread function mapping and gradient reversal
Authors: In Myung-Ho , Kang Daehun , Jo Hang Joon , Yarach Uten , Meyer Nolan K , Trzasko Joshua D , Huston John , Bernstein Matt A , Shu Yunhong 
Published: December 2022

Abstract

Objective. Interleaved reverse-gradient fMRI (RG-fMRI) with a point-spread-function (PSF) mapping-based distortion correction scheme has the potential to minimize signal loss in echo-planar-imaging (EPI). In this work, the RG-fMRI is further improved by imaging protocol optimization and application of reverse Fourier acquisition. Approach. Multi-band imaging was adapted for RG-fMRI to improve the temporal and spatial resolution. To better understand signal dropouts in forward and reverse EPIs, a simple theoretical relationship between echo shift and geometric distortion was derived and validated by the reliable measurements using PSF mapping method. After examining practical imaging protocols for RG-fMRI in three subjects on both a conventional whole-body and a high-performance compact 3 T, the results were compared and the feasibility to further improve the RG-fMRI scheme were explored. High-resolution breath-holding RG-fMRI was conducted with nine subjects on the compact 3 T and the fMRI reliability improvement in high susceptibility brain regions was demonstrated. Finally, reverse Fourier acquisition was applied to RG-fMRI, and its benefit was assessed by a simulation study based on the breath-holding RG-fMRI data. Main results. The temporal and spatial resolution of the multi-band RG-fMRI became feasible for whole-brain fMRI. Echo shift measurements from PSF mapping well estimated signal dropout effects in the EPI pair and were useful to further improve the RG-fMRI scheme. Breath-holding RG-fMRI demonstrated improved fMRI reliability in high susceptibility brain regions. Reverse partial Fourier acquisition omitting the late echoes could further improve the temporal or spatial resolution for RG-fMRI without noticeable signal degradation and spatial resolution loss. Significance. With the improved imaging scheme, RG-fMRI could reliably investigate the functional mechanisms of the human brain in the temporal and frontal areas suffering from susceptibility-induced functional sensitivity loss.
Markerless motion tracking with simultaneous MV and kV imaging in spine SBRT treatment—a feasibility study
Authors: Cai Weixing , Fan Qiyong , Li Feifei , He Xiuxiu , Zhang Pengpeng , Cervino Laura , Li Xiang , Li Tianfang 
Published: December 2022

Abstract

Objective. Motion tracking with simultaneous MV-kV imaging has distinct advantages over single kV systems. This research is a feasibility study of utilizing this technique for spine stereotactic body radiotherapy (SBRT) through phantom and patient studies. Approach. A clinical spine SBRT plan was developed using 6xFFF beams and nine sliding-window IMRT fields. The plan was delivered to a chest phantom on a linear accelerator. Simultaneous MV-kV image pairs were acquired during beam delivery. KV images were triggered at predefined intervals, and synthetic MV images showing enlarged MLC apertures were created by combining multiple raw MV frames with corrections for scattering and intensity variation. Digitally reconstructed radiograph (DRR) templates were generated using high-resolution CBCT reconstructions (isotropic voxel size (0.243 mm)3) as the reference for 2D–2D matching. 3D shifts were calculated from triangulation of kV-to-DRR and MV-to-DRR registrations. To evaluate tracking accuracy, detected shifts were compared to known phantom shifts as introduced before treatment. The patient study included a T-spine patient and an L-spine patient. Patient datasets were retrospectively analyzed to demonstrate the performance in clinical settings. Main results. The treatment plan was delivered to the phantom in five scenarios: no shift, 2 mm shift in one of the longitudinal, lateral and vertical directions, and 2 mm shift in all the three directions. The calculated 3D shifts agreed well with the actual couch shifts, and overall, the uncertainty of 3D detection is estimated to be 0.3 mm. The patient study revealed that with clinical patient image quality, the calculated 3D motion agreed with the post-treatment cone beam CT. It is feasible to automate both kV-to-DRR and MV-to-DRR registrations using a mutual information-based method, and the difference from manual registration is generally less than 0.3 mm. Significance. The MV-kV imaging-based markerless motion tracking technique was validated through a feasibility study. It is a step forward toward effective motion tracking and accurate delivery for spinal SBRT.
Feasibility of using a dual isocentre technique for treating cervical cancer on the 1.5 T MR-Linac
Authors: Chuter Robert W , Brewster Frank , Retout Louise , Cree Anthea , Aktürk Nesrin , Hales Rosie , Benson Rebecca , Hoskin Peter , McWilliam Alan 
Published: December 2022

Abstract

Objective. Patients treated for cervical cancer exhibit large inter and intra-fraction anatomical changes. The Unity MR-Linac (MRL) can image these patients with MR prior to and during treatment which enables daily plan adaptation. However, the MRL has a limited treatment field in the sup/inf direction of 22 cm which can restrict the treatment of patients who require longer treatment fields. Here we explore potential adaptive workflows in combination with a dual isocentre approach, to widen the range of cervix patients that can benefit from this treatment. Approach. Ten cervical cancer patients were retrospectively planned with a dual isocentre technique to deliver 45 Gy in 25 fractions. 5 node-negative and 5 node-positive patients were planned using the EMBRACE II protocol. A 2 cm overlap region between the two isocentres was positioned entirely in the nodal region. A treatment workflow was simulated to account for inter-fraction anatomical change. Isocentre shifts of 3 and 6 mm were applied to investigate the effect of intra-fraction motion. Main results. Dual isocentre adapted plans ensured significantly better coverage than non-adapted (recalculated) plans with a larger benefit seen for the node-negative cases. The difference to the reference plan for the V4275 cGy to the ITV was −0.8 cGy and −8.2 cGy for the adapted and recalculated plans respectively. Movements superiorly did not affect the coverage of the ITV by more than 1%, but shifting it inferiorly caused the ITV coverage on the plan to reduce by ∼2.4% per mm. Significance. A dual isocentre technique for cervical cancer treatments and adaptive workflows have been demonstrated to recover the required plan quality for inter-fraction changes. This illustrates the feasibility of a dual isocentre technique for the MRL.
Joint motion estimation and penalized image reconstruction algorithm with anatomical priors for gated TOF-PET/CT
Authors: Tsai Yu-Jung , Liu Chi 
Published: December 2022

Abstract
The presence of respiratory motion not only degrades the reconstructed image but also limits the utilization of anatomical priors in emission tomography. In this study, we explore the potential application of a joint motion estimation and penalized image reconstruction algorithm using anatomical priors in gated time-of-flight positron emission tomography/computed tomography (PET/CT). The algorithm is able to warp both the activity image and the attenuation map to align them with the measured data with the facilitation of anatomical information contained in the attenuation map. Five patient datasets, three acquired in single-bed position and two acquired in whole-body continuous-bed-motion mode, are included. For each patient, the attenuation map is derived from a breath-hold CT. The Parallel Levels Sets (PLS) is chosen as a representative anatomical prior. In addition to demonstrating the reliability of the estimated motion and the benefits of incorporating anatomical prior, preliminary results also indicate that the algorithm shows the potential to reconstruct an activity image in the space corresponding to that of the attenuation map, which could be applied to address the potential misalignment issue in applications involving multiple PET acquisitions but a single CT.
Dynamics of frustrated tunneling ionization driven by inhomogeneous laser fields
Authors: Xu Jingkun , Zhou Yueming , Li Yingbin , Liu Aihua , Chen Yongkun , Ma Xiaomeng , Huang Xiang , Liu Kunlong , Zhang Qingbin , Li Min , Yu Benhai , Lu Peixiang 
Published: December 2022

Abstract
We theoretically investigated frustrated tunneling ionization (FTI) driven by spatially inhomogeneous strong laser fields induced by surface plasmon resonance within a bow-tie metal nanostructure. The results show that the FTI probability and the principal quantum number distribution exhibit similar oscillatory behavior as a function of the pulse duration. Our analysis reveals that the periodic defocusing and refocusing of the electron spatial distribution due to the inhomogeneous laser field is responsible for the oscillatory structures. In addition, the initial tunneling coordinates and the angular momentum distributions of the FTI events and theirs pulse duration dependence are also explored. Moreover, our results show that the frequency of the oscillatory structures depends sensitively on the electron quiver amplitude and the inhomogeneity strength. Thus, the electron quiver amplitude and the size of the gap between bow-tie nanostructure are useful and efficient knobs for controlling the yield and properties of exited Rydberg states.
Resonant Kushi-comb-like multi-frequency radiation of oscillating two-color soliton molecules
Authors: Melchert O , Willms S , Oreshnikov I , Yulin A , Morgner U , Babushkin I , Demircan A 
Published: December 2022

Abstract
Nonlinear waveguides with two distinct domains of anomalous dispersion can support the formation of molecule-like two-color pulse compounds. They consist of two tightly bound subpulses with frequency loci separated by a vast frequency gap. Perturbing such a two-color pulse compound triggers periodic amplitude and width variations, reminiscent of molecular vibrations. With increasing strength of perturbation, the dynamics of the pulse compound changes from harmonic to nonlinear oscillations. The periodic amplitude variations enable coupling of the pulse compound to dispersive waves, resulting in the resonant emission of multi-frequency radiation. We demonstrate that the location of the resonances can be precisely predicted by phase-matching conditions. If the pulse compound consists of a pair of identical subpulses, inherent symmetries lead to degeneracies in the resonance spectrum. Weak perturbations lift existing degeneracies and cause a splitting of the resonance lines into multiple lines. Strong perturbations result in more complex emission spectra, characterized by well separated spectral bands caused by resonant Cherenkov radiation and additional four-wave mixing processes.
Spectral probing of an extremely compressed femtosecond wave packet in calcium fluoride
Authors: Geints I Y , Kompanets V O , Melnikov A A , Chekalin S V , Dormidonov A E , Kandidov V P 
Published: December 2022

Abstract
We use time-resolved spectral probing to study the dynamics of transformation of the optical properties of a nonlinear medium during formation and propagation of an extremely compressed mid-IR femtosecond wave packet in calcium fluoride. Broadening, attenuation and distortion of the probe pulse spectrum have been experimentally observed varying the delay time of the probe pulse relative to the pump. By solving the unidirectional pulse propagation equation that describes propagation and filamentation of a pump pulse in a calcium fluoride crystal we determine temporal changes of the refractive index and absorption coefficient induced by an extremely compressed wave packet. A mechanism of the observed broadening and breakup of the probe pulse spectrum is proposed.
Machine learning seizure prediction: one problematic but accepted practice
Authors: West Joseph , Dasht Bozorgi Zahra , Herron Jeffrey , Chizeck Howard J , Chambers Jordan D , Li Lyra 
Published: December 2022

Abstract

Objective. Epilepsy is one of the most common neurological disorders and can have a devastating effect on a person’s quality of life. As such, the search for markers which indicate an upcoming seizure is a critically important area of research which would allow either on-demand treatment or early warning for people suffering with these disorders. There is a growing body of work which uses machine learning methods to detect pre-seizure biomarkers from electroencephalography (EEG), however the high prediction rates published do not translate into the clinical setting. Our objective is to investigate a potential reason for this. Approach. We conduct an empirical study of a commonly used data labelling method for EEG seizure prediction which relies on labelling small windows of EEG data in temporal groups then selecting randomly from those windows to validate results. We investigate a confound for this approach for seizure prediction and demonstrate the ease at which it can be inadvertently learned by a machine learning system. Main results. We find that non-seizure signals can create decision surfaces for machine learning approaches which can result in false high prediction accuracy on validation datasets. We prove this by training an artificial neural network to learn fake seizures (fully decoupled from biology) in real EEG. Significance. The significance of our findings is that many existing works may be reporting results based on this confound and that future work should adhere to stricter requirements in mitigating this confound. The problematic, but commonly accepted approach in the literature for seizure prediction labelling is potentially preventing real advances in developing solutions for these sufferers. By adhering to the guidelines in this paper future work in machine learning seizure prediction is more likely to be clinically relevant.