bluuebunny/crossref_metadata_2025_split huggingface dataset:
All-organic flexible heterojunction thin film photodetectors based on phthalocyanines/C60
Authors: Zhang Xiaoqiang , Gao Huiying , Yang Ming , Jiang Hao , Li Zhoushuo 
Published: August 2022

In modern organic photoelectric detection, a broad spectrum response is much needed. Unfortunately, it remains a huge challenge in the field of optoelectronics. In this work, a photodetector based on phthalocyanines/C60 thin film heterojunction was fabricated by in situ secondary evaporation. Most encouragingly, the device has no selectivity to the substrate and can grow well on the flexible substrate, and the performance of the device changes merely 7.27% after 104 bending cycles, which shows its stability performance. The device has the ability to detect a wide band from visible light to near infrared. The largest Ri of the device was obtained reaching up to 0.94 A W−1, with crest value D* equals to 4.7 × 1012 Jones. The all-organic heterojunction devices prepared by us have the advantages of simple preparation method, low cost, and no selectivity to the substrate, which shows a very good application potential in the fields of flexible wearable and infrared remote sensing imaging in the future.
Subpetahertz helicity modulation of attosecond pulse train using detuned two-color fields
Authors: Sun Ning , Chen Yuantong , Chen Yuhang , Zhu Xiaosong 
Published: August 2022

Abstract
We theoretically demonstrate a scheme to obtain an attosecond pulse train with subpetahertz helicity modulation, based on high harmonic generation driven by detuned two-color fields. As the waveform of the detuned two-color field varies with time, the attosecond pulse train switches periodically between left and right elliptical polarization in the temporal domain. The frequency of the helicity modulation can reach subpetahertz. In addition, by adjusting the frequency detuning of the two-color field, the modulation frequency can be continuously controlled. The scheme is expected to provide a useful light source to explore and manipulate a wide range of ultrafast dynamics in magnetic materials and chiral molecules.
Fault diagnosis of bearings in multiple working conditions based on adaptive time-varying parameters short-time Fourier synchronous squeeze transform
Authors: Wei Minghui , Yang Jianwei , Yao Dechen , Wang Jinhai , Hu Zhongshuo 
Published: August 2022

Abstract
Rolling bearings are commonly used components in rotating machinery and play a vital role. When the bearing fails, if it cannot be found and repaired in time, it will cause great economic losses. Time-frequency analysis has been widely used for bearing fault signals under non-stationary operating conditions, but the existing methods have problems such as poor adaptability under multiple operating conditions. At the same time, the low time-frequency resolution and poor energy aggregation also affect the fault feature extraction effect. Aiming at these problems, this paper proposes a bearing fault detection method, which combines empirical mode decomposition and adaptive time-varying parameter short-time Fourier synchronous squeezing transform (AFSST), it solves the problem of adapting to signals under multiple operating conditions; A weighted least squares estimation time-varying parameter algorithm is proposed, which improves the calculation speed by 29% under the premise of ensuring the calculation accuracy; A time-varying index of energy effective compression ratio is proposed to accurately measure the time-varying energy aggregation of time-frequency analysis methods. Using short-time Fourier transform, continuous wavelet transform, wavelet synchrosqueezed transform, and AFSST to analyze the simulated FM signal, the results show that the AFSST transform has better time-frequency resolution and higher energy-efficient compression rate globally. Through the verification of the fault experimental data of rolling bearings, the diagnosis method proposed in this paper can accurately extract the bearing fault characteristics, has a good diagnosis ability in the multi-working operating environment, and has strong robustness and anti-noise interference.
Sub-wavelength focusing for low-frequency sound sources using an iterative time reversal method
Authors: Li Yuanwen , Li Min , Pan Wei , Feng Daofang , Yang Debin 
Published: August 2022

Abstract
Microphone array measurements processed with imaging algorithms are commonly performed to identify and quantify noise sources in machines, which is the premise of noise control. However, due to the limitations of the half-wavelength theory, beamforming and time reversal (TR) methods cannot effectively separate multiple low-frequency sources. Although near-field acoustic holography can overcome the diffraction limit, it will encounter an ill-posed problem. To avoid solving the inverse problem, iterative TR processing (iterative-TR) is proposed to obtain the sub-wavelength focusing and improve the spatial resolution at low frequency. The focusing result is corrected step by step with iteration implemented until it reaches the convergence threshold. The propagation matrix between microphones and focusing points is reconstructed by singular-value normalization to ensure the convergence of the iteration. Numerical simulation results show that the iterative-TR method is able to break through the diffraction limit below 1000 Hz within a measurement distance of 0.5 m and reach convergence within 105 iterations, which is less than 10 s. The experimental results indoors with significant reverberation show that iterative-TR has the ability to stably give the multiple source positions with 0.11 m spacing even at 100 Hz, that is, the spatial resolution reaches 1/31 wavelength. Detailed analysis shows that the overall performance of iterative-TR outperforms other methods capable of sub-wavelength focusing for signals below 1000 Hz. The identification of two loudspeakers in a car shows the practicality of the proposed method.
An exploratory study of machine learning techniques applied to therapeutic energies particle tracking in microdosimetry using the novel hybrid detector for microdosimetry (HDM)
Authors: Missiaggia Marta , Pierobon Enrico , La Tessa Chiara , Cordoni Francesco G 
Published: August 2022

Abstract
In this work we present an advanced random forest-based machine learning (ML) model, trained and tested on Geant4 simulations. The developed ML model is designed to improve the performance of the hybrid detector for microdosimetry (HDM), a novel hybrid detector recently introduced to augment the microdosimetric information with the track length of particles traversing the microdosimeter. The present work leads to the following improvements of HDM: (i) the detection efficiency is increased up to 100%, filling not detected particles due to scattering within the tracker or non-active regions, (ii) the track reconstruction algorithm precision. Thanks to the ML models, we were able to reconstruct the microdosimetric spectra of both protons and carbon ions at therapeutic energies, predicting the real track length for every particle detected by the microdosimeter. The ML model results have been extensively studied, focusing on non-accurate predictions of the real track lengths. Such analysis has been used to identify HDM limitations and to understand possible future improvements of both the detector and the ML models.
Development of controller for fast plasma position control coils with ISO-FLUX scheme on JT-60SA
Authors: Kojima S , Inoue S , Miyata Y , Urano H , Suzuki T 
Published: August 2022

Abstract
Two types of poloidal magnetic field coils, superconducting poloidal field (SCPF) coils and in-vessel coils called fast plasma position control (FPPC) coils, will be installed in JT-60SA. We presented the different roles of SCPF and FPPC coils. The SCPF coils control plasma position and shape (P/S) and plasma current (I
p), whereas the FPPC coils stabilize the perturbation of the n= 0 mode of magnetohydrodynamic (MHD) instability, such as vertical instability. This study developed a controller that outputs a coil voltage command for the power supply connected to each coil based on an ISO-FLUX scheme using an equilibrium control simulation code, MHD equilibrium control simulator (MECS). This controller stabilizes the horizontal and vertical plasma displacements using FPPC coils. FPPC coils have the advantage of FPPC due to fast coil current response; however, the induced current is also driven in FPPC coils. Thus, we proposed a control logic to mitigate the induced currents, particularly when the induced voltage is large. The difference in coil current response for SCPF and FPPC coils causes the coupling problem. Thus, decoupling between the SCPF and FPPC coils was established by employing the derivative treatment on the ISO-FLUX scheme in the FPPC control. To investigate the effectiveness of the FPPC control, using MECS we evaluated the allowable I
p disruption intensity, which causes the plasma horizontal displacement, in the high elongation plasma, which relates to the plasma vertical displacement. Higher I
p disruption intensity and elongation were allowed by adding the FPPC control. We investigated the controllability in the plasma ramp-up and flat-top operations. The support of FPPC control for SCPF control expands the plasma operation region which contributes to achieving the planned plasma operation in JT-60SA.
Application of deep learning to soft x-ray tomography at EAST
Authors: Mai Chaowei , Hu Liqun , Xu Liqing , Chao Yan , Chen Kaiyun , Chen Yiping 
Published: August 2022

Abstract
Soft x-ray (SXR) cameras in a tokamak are limited spatially by ports of the vacuum vessel, and SXR tomography (SXT) technology is developed for reconstructing a two-dimensional SXR profile. However, traditional SXT is time-consuming and has difficulty achieving abundant and quick reconstructions for a tokamak. Based on experimental SXR data and Fourier–Bessel SXT codes at the EAST tokamak, three typical neural networks are built and trained. All the trained neural networks complete reconstruction within several milliseconds on a personal computer and succeed in constraining the SXR profile to match most of the data. In particular, the best-performing fully convolutional neural network provides SXR reconstruction images on the 2D evolution of a sawtooth, and shows its generalization. In the future, it is possible to provide an outstanding deep learning substitute to give abundant and quick SXT images instead of traditional SXT, after training for a few days.
Nonlocal Timoshenko shear beam model for multilayer curved graphene nano-switches
Authors: Koochi Ali , Yaghoobi Majid 
Published: August 2022

Abstract
Graphene sheets are the basis of nano-electromechanical switches, which offer a unique insight into the world of quantum mechanics. In this paper, we proposed a new size-dependent multi-beam shear model for investigating the pull-in instability of multilayer graphene/substrate nano-switches within the context of the Timoshenko beam theory. As the graphene/substrate bemas bent toward the graphene layer due to the thermomechanical mismatch, the impact of curvature is considered in the proposed model. Also, the impact of the Casimir attraction is incorporated in the developed model by taking into account the limited conductivity of interacting surfaces. The scale dependency of the materials is considered in the framework of the nonlocal elasticity. To simulate the nano-switch and explore the pull-in instability, a finite element procedure is developed. The proposed approach is verified by comparing the pull-in voltage to published data. Finally, the role of influential parameters, including size dependency, length, initial gap, curvature, and the number of graphene layers on instability voltage of nano-switch, are investigated.
Self-interacting dark scalar spikes around black holes via relativistic Bondi accretion
Authors: Feng Wei-Xiang , Parisi Alessandro , Chen Chian-Shu , Lin Feng-Li 
Published: August 2022

Abstract
We consider the spike mass density profile in a dark halo by self-consistently solving the relativistic Bondi accretion of dark matter onto a non-spining black hole of mass M. We assume that the dominant component of the dark matter in the halo is a Standard model gauge-singlet scalar. Its mass m ≃ 10-5 eV and quartic self-coupling λ ≲ 1019 are constrained to be compatible with the properties of galactic dark halos. In the hydrodynamic limit, we find that the accretion rate is bounded from below, M
min = 96πG
2
M
2
m
4/λħ
3. Therefore, for M = 106
M⊙ we have M
min ≃ 1.41 × 10-9
M
⊙ yr-1, which is subdominant compared to the Eddington accretion of baryons. The spike density profile ρ
0(r) within the self-gravitating regime cannot be fitted well by a single-power law but a double-power one. Despite that, we can fit ρ
0(r) piecewise and find that ρ
0(r) ∝ r
-1.20 near the sound horizon, ρ
0(r) ∝ r
-1.00 towards the Bondi radius and ρ
0(r) ∝ r
-1.08 for the region in between. This contrasts with more cuspy ρ
0(r) ∝ r
-1.75 for dark matter with Coulomb-like self-interaction.
Simulations of charge collection of a gallium nitride based pin thin-film neutron detector
Authors: Zhang Z. , Aspinall M. 
Published: August 2022

Abstract
The development of new fast neutron reactors and nuclear fusion reactors requires new neutron detectors in extreme environments. Due to its wide bandgap (3.4 eV) and radiation resistance capability, gallium nitride (GaN) is a candidate for neutron detection in extreme environments. This study introduces a novel simulation method of charge collection efficiency (CCE) for GaN pin thin-film neutron detector based on the Hecht equation and Monte Carlo simulation. A modified 2-carrier Hecht equation is used to simulate the CCE of the detector with a different depth depletion region. After obtaining the neutron energy deposition distribution in the sensitive volume of the detector, the Hecht equation is used to calculate the charge collection efficiency at different positions of the detector under a uniform electric field. The maximum relative error between the simulated CCE and the experimental CCE value is about 6.3%.
Committed to restoring tropical forests: an overview of Brazil’s and Indonesia’s restoration targets and policies
Authors: Dockendorff Constantino , Fuss Sabine , Agra Raquel , Guye Valentin , Herrera Diego , Kraxner Florian 
Published: August 2022

Abstract
The restoration of tropical forests has become a popular nature-based solution for climate change mitigation, protection of biodiversity, and improving the livelihoods of local populations. The Bonn Challenge and the UN Decade on Ecosystem Restoration underscore the international momentum of the restoration movement, with many countries committing to restore millions of hectares of deforested and degraded land in the next decade. Brazil and Indonesia are among the ones with the most ambitious restoration commitments globally. Since both their economies are highly dependent on the export of agricultural commodities, reconciling economic growth with environmental sustainability will be a major policy challenge. In this paper, we (a) identify the main restoration targets and the policies supporting their implementation in both countries, (b) provide a descriptive overview of these restoration-supportive policies, and (c) discuss the main challenges that Brazil and Indonesia face in the implementation of their restoration commitments. We find that Brazil has an explicit and dedicated strategy to achieve its restoration target, but that recent political developments have weakened environmental governance in the country, affecting the implementation of its restoration commitment. In the case of Indonesia, we find that the government has rather focused and progressed on the restoration of peatlands and mangroves, whereas its commitment to restore forestlands has yet to benefit from a dedicated plan that allows to coordinate policies and agencies’ efforts towards the achievement of its restoration target.
DhMYB22andDhMYB60regulate pigment intensity and floral organ shape inDendrobiumhybrid
Authors: Khairul-Anuar Muhammad-Asyraf , Mazumdar Purabi , Othman Rofina Yasmin , Harikrishna Jennifer Ann 
Published: August 2022

AbstractBackgroundFlower pigment and shape are determined by the coordinated expression of a set of structural genes during flower development. R2R3-MYB transcription factors are known regulators of structural gene expression. The current study focused on two members of this large family of transcription factors that were predicted to have roles in pigment biosynthesis and organ shape development in orchids.MethodsPhylogenetic analysis was used to identify candidate Dendrobium catenatum R2R3-MYB (DcaMYB) sequences associated with pigment and cell shape development. Gene silencing of candidate DhMYBs in Dendrobium hybrid by direct application of dsRNA to developing flowers was followed by observation of gene expression level and flower phenotypes. Silencing of the structural gene chalcone synthase was used as a comparative control.Key ResultsTen candidate flower-associated DcaMYBs were identified. Flowers treated with dsRNA of DhMYB22 and DhMYB60 sequences were less pigmented and had relatively low expression of anthocyanin biosynthetic genes (F3ʹH and DFR), lower total anthocyanin concentration and markedly lower levels of cyanidin-3-glucoside and cyanidin-3-rutinoside. Petals of DhMYB22-treated flowers and sepals of DhMYB60-treated flowers showed the greatest colour difference relative to the same organs in untreated flowers. DhMYB22-treated flowers had relatively narrow and constricted lips, while DhMYB60-treated flowers had narrow and constricted sepals. No significant difference in shape was observed for DhCHS-treated or untreated flowers.ConclusionsOur results demonstrate that DhMYB22 and DhMYB60 regulate pigment intensity and floral organ shape in Dendrobium. This is a first report of MYB regulation of floral organ shape in orchids.
Phylogeography of the mesic-adapted striped mouse,Rhabdomys dilectus chakae(Rodentia: Muridae) in forest margins of the Eastern Cape and southern KwaZulu-Natal provinces of South Africa
Authors: Matamba Emmanuel , Richards Leigh R , Cherry Michael I , Rambau Ramugondo V 
Published: August 2022

AbstractRhabdomys is a genus that occupies a variety of habitats, including forest margins. Among the Rhabdomys taxa, Rhabdomys dilectus chakae has a distribution that covers the eastern seaboard of South Africa, with a poorly defined divergence date from its sister taxon Rhabdomys dilectus dilectus. Here, we study three mitochondrial markers (cytochrome b, cytochrome c oxidase I and partial control region) of R. d. chakae across the Eastern Cape and KwaZulu-Natal forests of South Africa, aiming to determine the cladogenesis (molecular dating) and effective population size of this subspecies through time, in addition to its cladogenesis in relationship to other species within the genus. A phylogenetic analysis revealed six clades within Rhabdomys, confirming that our study area is occupied solely by R. d. chakae, to the exclusion of other recognized sibling species. A fossil-calibrated Bayesian relaxed molecular clock estimated a recent split between R. d. chakae and R. d. dilectus ~1.4 ± 0.35 Mya and between two Rhabdomys pumilio groups, coastal A and B, at 1.16 ± 0.44 Mya. Coalescent Bayesian skyline plots revealed a stable population of R. d. chakae in the study area that was in slow decline until 2500 years ago, when there was an expansion in the late Holocene. Radiation within Rhabdomys dates as far back as 4.27 Mya, and subsequent demographic fluctuations primarily reflect palaeoclimatic changes.
Investigation of the optimal culture time for warmed bovine ovarian tissues before transplantation
Authors: Meng Lingbo , Sugishita Yodo , Nishimura Sandy , Uekawa Atsushi , Suzuki-Takahashi Yuki , Suzuki Nao 
Published: August 2022

Abstract
Ovarian tissue cryopreservation by vitrification is an effective technique, but there are still many unresolved issues related to the procedure. The aim of this study was to investigate the optimal culture time of postwarmed ovarian tissues and their viability before ovarian tissue transplantation. The bovine ovarian tissues were used to evaluate the effect of postwarming culture periods (0, 0.25, 0.5, 1, 2, 5, and 24 h) in the levels of residual cryoprotectant, LDH release, ROS generation, gene and protein abundance, and follicle viability and its mitochondrial membrane potential. Residual cryoprotectant concentration decreased significantly after 1 h of culture. The warmed ovarian tissues that underwent between 0 and 2 h of culture time showed similar LDH and ROS levels compared with fresh nonfrozen tissues. The anti-Mullerian hormone transcript abundance did not differ in any of the groups. No increase in the relative transcript abundance and protein level of Caspase 3 and Cleaved-Caspase 3, respectively, in the first 2 h of culture after warming. On the other hand, an increased protein level of double stranded DNA breaks (gamma-H2AX) was observed in postwarmed tissues disregarding the length of culture time, and a temporary reduction in pan-AKT was detected in postwarming tissues between 0 and 0.25 h of culture time. Prolonged culture time lowered the percentage of viable follicles in warmed tissues, but it did not seem to affect the follicular mitochondrial membrane potential. In conclusion, 1–2 h of culture time would be optimal for vitrified-warmed tissues before transplantation.
Reducing Suicide-Related Stigma through Peer-to-Peer School-Based Suicide Prevention Programming
Authors: Wright-Berryman Jennifer L , Thompson Devyn , Cramer Robert J 
Published: August 2022

Abstract
Youth suicide rates have consistently risen over the past decade, and stigma related to mental health may create a barrier to young people seeking help. Schools are a common intercept point for mental health and suicide prevention programming. Hope Squad, a school-based, peer-to-peer, suicide prevention program, uses trained and mentored students nominated by their peers to perform intentional outreach with fellow students. When a Hope Squad member detects a mental health or suicide crisis in a peer, they alert a trusted adult. We employed a cohort, wait-list–control, cross-sectional survey design. We recruited more than 3,400 students from nine schools—five with Hope Squads and four without—to observe differences in student-body suicide-related stigma. At the end of the academic year, there was significantly lower stigma in Hope Squad schools versus those without the program. Findings suggest that a peer-to-peer, school-based, suicide prevention program may reduce stigmatizing attitudes related to suicide. Next steps include a randomized controlled trial to identify changes in help-seeking and similar protective factors.