bluuebunny/crossref_metadata_2025_split huggingface dataset:
Suppressing image blurring of PROPELLER MRI via untrained method
Authors: Saju Gulfam , Li Zhiqiang , Mao Hui , Liu Tianming , Chang Yuchou 
Published: July 2023

Abstract

Objective. Periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) used in magnetic resonance imaging (MRI) is inherently insensitive to motion artifacts but with an expense of around 60% increase in minimum scan time. An untrained deep learning method is proposed to accelerate PROPELLER MRI while suppressing image blurring. Approach. Several reconstruction methods have been developed to accelerate PROPELLER with reduced sampling on blades. However, image quality is degraded due to blurring. Deep learning has been applied to enhance MRI reconstruction quality, and external training data are therefore needed. In addition, the distribution shift problem in deep learning also exists between the external training data and to-be-reconstructed target blade data. This paper introduces an untrained neural network (UNN) to suppress image blurring, which is applied to improve PROPELLER MRI. This network structure was then incorporated into blade k-space. Results. The untrained method improved the blade image quality from brain MRI data. Furthermore, it enhanced the sharpness of the reconstructed image compared to PROPELLER reconstructions using parallel imaging methods and supervised learning methods using external training data. PROPELLER blade acquisition was accelerated by undersampling data with reduction factors 2, 3 and 4. Significance. The reported UNN enhanced PROPELLER method can improve image quality by suppressing blurring. External training data are not needed to mitigate the challenge of collecting high-quality clinical data for training without affecting clinical workflow and the standard care for patients.
Verification of gyrokinetic particle simulations of neoclassical tearing modes in fusion plasmas
Authors: Wang Kaijie , Sun Shuying , Zhang Wenlu , Lin Zhihong , Wei Xishuo , Liu Pengfei , Feng Hongying , Wang Xiaogang , Li Ding 
Published: July 2023

Abstract
The ability to simulate neoclassical tearing modes (NTMs) in the gyrokinetic toroidal code (GTC) has been developed and verified, in which ions are treated with a gyrokinetic model and electrons are treated as a resistive fluid. The simulation results demonstrate that the neoclassical bootstrap current effect can destabilize an otherwise stable classical tearing mode. In the cylindrical geometry, GTC simulations in the magnetohydrodynamic limit show quantitative agreement with the modified Rutherford theory, both in terms of the scaling law in the small island limit and in terms of the saturation level and pressure flattening effect in the large island limit. The toroidal effects are slightly destabilizing for the NTM, while the kinetic effects of thermal ions are stabilizing for the NTM and increase its excitation threshold.
High infrared responsivity of silicon photodetector with titanium-hyperdoping
Authors: Cheng Li , Yang Lei , Fu Jiawei , Cong Jingkun , Yang Deren , Yu Xuegong 
Published: July 2023

Abstract
Silicon (Si) photodetectors have advantages of low cost, convenient preparation, and high integration. However, limited by the indirect bandgap of 1.12 eV, Si photodetectors cannot perform at the wavelength beyond 1100 nm. It is attractive to extend the response wavelength of Si-based photodetectors for the optoelectronics application in recent years. In this article, we have successfully prepared a high-performance photoconductive detector based on titanium-hyperdoped Si (Si:Ti). The Si:Ti material shows an enhanced infrared absorption primarily attributed to the sub-bandgap photo excitation assisted by titanium (Ti)-induced energy states with an average energy level of Ev + 0.23 eV. Moreover, the detector exhibits a high responsivity of 200 mA W−1 under 1550 nm light at 5 V bias, which is higher than previously reported transition metals hyperdoped silicon detectors. These results are helpful for the development of infrared hyperdoped silicon photodetectors in the field of optoelectronics.
Growth simulation based on diffusion-limited aggregation method for dendritic interfacial electrodes inside IPMC
Authors: Zhao Chun , Yan Yuting , Tang Gangqiang , Zhao Xin , Mei Dong , Wang Yanjie 
Published: July 2023

Abstract
Ionic polymer metal composites (IPMCs) with dendritic interfacial electrodes (DIEs) have attracted attention in recent years due to their excellent actuation performance. Although considerable efforts have been made to develop aggregation models of metal particles for the electrode formation of IPMC, there are few reports to simulate the growth of DIEs inside IPMC. In this work, we proposed an electrode model based on diffusion-limited aggregation method to simulate the growth process of DIEs inside IPMC by referring their preparation parameters and morphology characteristics. Meanwhile, the effects of immersion reduction (IR) cycles, immersion electroplating (IEP) time, IEP cycles, current intensity and voltage amplitude on the morphology and microstructure of DIEs were studied. It was found that the depth and the density of DIEs inside IPMC gradually increased with the increase of IR cycles, IEP time and IEP cycles. However, the growth depth of DIEs decreased significantly with the increase of current intensity. In addition, the voltage amplitude has little effect on the DIEs. This model is of great significance to the study of the formation mechanism of IPMC with DIEs.
Charge-plasma-based inverted T-shaped source-metal dual-line tunneling FET with improved performance at 0.5 V operation
Authors: Anam Aadil , Amin S Intekhab , Prasad Dinesh , Kumar Naveen , Anand Sunny 
Published: July 2023

Abstract
In this paper, a charge plasma-based inverted T-shaped source-metal dual line-tunneling field-effect transistor (CP-ITSM-DLTFET) has been proposed to improve the ON current (ION) by increasing the line-tunneling area. In the proposed structure, the charge plasma technique is used to induce the dopants in the source and drain regions. Due to its doping-less structure, the proposed CP-ITSM-DLTFET is immune to random dopant fluctuations and does not require an expensive thermal annealing technique. This makes the proposed device’s fabrication easier and more efficient. The proposed CP-ITSM-DLTFET comprises an inverted T-shaped source metal (sandwiched between the Si-channel) and creates gate-to-source overlap and increases the tunneling area vertically on both sides of the Si-channel. The vertical line-tunneling area in the proposed structure makes the device able to be aggressively scaled compared to conventional TFETs for future technology. The proposed CP-ITSM-DLTFET outperforms almost all pre-existing dopingless TFETs in terms of DC and RF parameters. The switching performance (like high ION = 31.88 uA um−1, steeper AVSS = 23.42 mV dec−1 (over 12-order of drain current), and high ION/IOFF ratio of 1.6 × 1013) and the RF performance (like transconductance (gm) = 0.37 mS, Cut-off frequency (fT) = 90.18 GHz, and Gain Bandwidth product (GBW) = 32.3 GHz) of the proposed CP-ITSM-DLTFET are superior to almost all pre-existing Si, SiGe, and Ge based doping-less TFETs. Moreover, the proposed CP-ITSM-DLTFET-based CMOS inverter has also been comprehensively studied in the paper, showing a good noise margin NMH = 0.198 V (39.8% of VDD) and NML = 0.206 V (41.2% of VDD) with a high voltage gain of 30.25 at VDD = 0.5 V, suggesting great potential for future low power applications.
An approach of filtering simulated magnetospheric X-ray images based on self-supervised network and random forest
Authors: Wang Jiaqi , Wang Rongcong , Li Dalin , Sun Tianran , Peng Xiaodong 
Published: July 2023

AbstractImaging is an important method for observing the Earth’s space environment. Future missions, such as the Solar wind Magnetosphere Ionosphere Link Explorer (SMILE), aim to explore the interaction between the solar wind and the Earth’s magnetosphere via soft x-ray imaging. With the advent of these missions, a large number of magnetospheric images may be acquired. However, as the viewing geometry and solar wind conditions change, satellites sometimes fail to capture the magnetopause inside the field of view. We propose an approach that blends machine learning and deep learning to filter the simulated x-ray images for the SMILE mission, aiming to achieve automatic classification of the detected images. First, we performed magnetohydrodynamic simulations to derive the predicted SMILE x-ray images. Then, we used a self-supervised contrast feature extraction network to study the features of the images. Using this network, the random forest classifier can distinguish whether the subsolar point at the magnetopause has been detected. Finally, we designed the magnetopause filter to obtain the subsolar magnetopause images with observation positions outside the magnetosphere. As a result, the prediction accuracy of the classifier is up to 93%. And the F1 score is up to 95.5%. The stratified predictions allow an automatic screening of whether satellite magnetospheric images cover the subsolar magnetopause. These images, which have observation positions outside the magnetosphere, can be used to invert the three-dimensional magnetopause.
Alcubierre warp drive in Bohmian Quantum Gravity
Authors: Joseph Sijo K 
Published: July 2023

Abstract
In the realm of theoretical physics, the Alcubierre warp drive metric has long been a topic of fascination. However, the feasibility of this seemingly miraculous method of faster-than-light travel has been limited by the requirement of exotic matter, which has proven elusive to obtain. This research has revealed a potential breakthrough in the quest for exotic matter, through the coupling of the Alcubierre warp drive metric to a quantum mechanical scalar matter field. By mapping the requirement of exotic matter into a conformal wave equation, it becomes possible to express the problem as a fourth-order partial differential equation in terms of the quantum mechanical density. This research reveals that the key to solving the exotic matter problem lies in finding a proper quantum mechanical density that satisfies the proposed partial differential equation.
Optimal mass on the parabolic-elliptic-ODE minimal chemotaxis-haptotaxis in
R2
Authors: Li Siying , Wang Jinhuan 
Published: July 2023

Abstract
In this paper, we study the Cauchy problem to a chemotaxis-haptotaxis model describing cancer invasion in

R

2

. The main feature is to prove that 8π is the critical mass on initial data for distinguishing existence and blow-up of solutions to the model. Namely, when the initial mass is less than 8π, we prove global existence of solutions by constructing a proper free energy and using the Brezis-Merle type inequality. On the contrary, the finite time blow-up of solutions may occur if the initial mass is greater than 8π and the initial second moment is small enough. Comparing to the classical Keller-Segel model, we find that the haptotaxis has no effect on the critical mass of the model.
Consistency tests of field level inference with the EFT likelihood
Authors: Kostić Andrija , Nguyen Nhat-Minh , Schmidt Fabian , Reinecke Martin 
Published: July 2023

AbstractAnalyzing the clustering of galaxies at the field level in principle promises access to all the cosmological information available. Given this incentive, in this paper we investigate the performance of field-based forward modeling approach to galaxy clustering using the effective field theory (EFT) framework of large-scale structure (LSS). We do so by applying this formalism to a set of consistency and convergence tests on synthetic datasets. We explore the high-dimensional joint posterior of LSS initial conditions by combining Hamiltonian Monte Carlo sampling for the field of initial conditions, and slice sampling for cosmology and model parameters. We adopt the Lagrangian perturbation theory forward model from [1], up to second order, for the forward model of biased tracers. We specifically include model mis-specifications in our synthetic datasets within the EFT framework. We achieve this by generating synthetic data at a higher cutoff scale Λ0, which controls which Fourier modes enter the EFT likelihood evaluation, than the cutoff Λ used in the inference. In the presence of model mis-specifications, we find that the EFT framework still allows for robust, unbiased joint inference of a) cosmological parameters — specifically, the scaling amplitude of the initial conditions — b) the initial conditions themselves, and c) the bias and noise parameters. In addition, we show that in the purely linear case, where the posterior is analytically tractable, our samplers fully explore the posterior surface. We also demonstrate convergence in the cases of nonlinear forward models. Our findings serve as a confirmation of the EFT field-based forward model framework developed in [2-7], and as another step towards field-level cosmological analyses of real galaxy surveys.
IWDM: the fate of an interacting non-cold dark matter — vacuum scenario
Authors: Pan Supriya , Yang Weiqiang , Di Valentino Eleonora , Mota David F. , Silk Joseph 
Published: July 2023

Abstract
In most cosmological models, the equation of state of the dark matter is assumed to be zero, which means that the dark matter is pressure-less or cold. While this hypothesis is based on the abundance of cold dark matter in the universe, however, there is no compelling reason to assume that the equation of state of dark matter is exactly zero. A more general approach would be to allow for a range of values for the dark matter equation of state and use the observational data to determine which values are most likely. With the increasing accuracy of experimental data, we have chosen to explore the possibility of interacting non-cold dark matter - vacuum scenario, where the equation of state of the dark matter is constant but can take different values within a specific range. Using the Cosmic Microwave Background (CMB) anisotropies and the CMB lensing reconstruction from the Planck legacy release, plus other non-CMB measurements, namely, the baryon acoustic oscillations distance measurements, and the Pantheon catalogue from Type Ia Supernovae, we have analyzed this scenario and found that a non-zero value for the dark matter equation of state is preferred with a confidence level of over 68%. While this is not significant by itself, however, it does suggest that investigating the possibility of non-cold dark matter in the universe is worth exploring further to gain a better understanding of the nature of dark matter.
High-efficiency Ho:YAG single-crystal fiber laser in-band pumped by a 1.9 μm laser diode
Authors: Wang Jianlei , Dong Jifei , Liu Jian , Wang Zhanxin , Xu Xiaodong , Xu Jun , Zhao Yongguang , Wang Chun 
Published: July 2023

Abstract
We report on a 10-watt-level, efficient 2 μm Ho:YAG (0.6 at.% Ho3+ doped Y3Al5O12) single crystal fiber (SCF) laser in-band pumped by a 1.9 μm laser diode. Benefiting from the high gain of the SCF and the unique propagation features of the pump and laser beams, a maximum output power of 10.77 W is achieved with T
OC = 20%, corresponding to a slope efficiency of 61.8%. The higher efficiency of 64.8% and the output power of 9.8 W are obtained with T
OC = 50%. Compared to the traditional bulk crystal, wave-guiding of the pump light in the SCF can extend the gain region and thus improve the laser efficiency, which provides a simple and effective method to improve the utilization rate of the pump light even for the low-brightness laser diodes.
Clinical impacts of frailty on 123,172 people with diabetes mellitus considering the age of onset and drugs of choice: a nationwide population-based 10-year trajectory analysis
Authors: Huang Shih-Tsung , Chen Liang-Kung , Hsiao Fei-Yuan 
Published: July 2023

Abstract

Aims
Frailty substantially increased the risk of adverse clinical outcomes, which was also critical in diabetes management. This study aimed to investigate the interrelationships between the age of onset, frailty, anti-diabetic medications and clinical outcomes in people with diabetes mellitus (DM).

Methods
A total of 123,172 people aged 40 years and older who were newly diagnosed with DM were identified and categorised into four frailty subgroups (robust, mild, moderate and severe) based on the multimorbidity frailty index (mFI). Cox proportional hazards models were used to examine associations between frailty and clinical outcomes at different ages of DM onsets (40–64, 65–74, 75–84 and 85+ years). Outcomes of interest included generic outcomes (mortality and unplanned hospitalisation) and DM-related outcomes (cardiovascular disease-related mortality, major adverse cardiovascular events (MACEs), diabetes-related hospitalisation and hypoglycaemia).

Results
The proportion of frailty increased with age at diagnosis amongst people with incident DM and the mFI scores increased significantly during the 10-year follow-up. Amongst people with diabetes, those with mild, moderate and severe frailty were associated with greater risks of all-cause mortality (mild: adjusted hazard ratio (aHR) 1.69 [95% confidence interval (CI) 1.60–1.80], P &lt; 0.01; moderate: aHR 2.46 [2.29–2.65], P &lt; 0.01; severe frailty: aHR 3.40 [3.16–3.65], P &lt; 0.01) compared with the robust group. Similar results were found in unplanned hospitalisations, cardiovascular disease-related mortality, MACEs and hypoglycaemia.

Conclusions
Our study quantified the prevalence of frailty, captured its dynamic changes and examined its impacts on various clinical outcomes amongst people with diabetes at different ages at onset. Frailty assessment and management should be implemented into routine diabetes care.
Aesthetic Breast Surgery: What Do the Measurements Reveal? A Practical Visual Application of the Results
Authors: Bolletta Elisa , McGoldrick Ciara , Hall-Findlay Elizabeth J 
Published: July 2023

Abstract

Background
The results of preoperative and 1-year postoperative measurements in aesthetic breast surgery were outlined in chart form in the Aesthetic Surgery Journal in 2020. Measurements were performed preoperatively and postoperatively, but the authors concentrated on 1-year follow-up because it was generally accepted as the minimum time to define a stable surgical result. Extensive statistical analysis was outlined in the previous paper.

Objectives
This paper translates those results into a visual form so that the surgeon can see the changes that occur in breast reduction, breast augmentation, mastopexy, mastopexy-augmentation, and implant removal with mastopexy.

Methods
There were 548 patients in the breast augmentation group, 388 patients in the breast reduction group, 244 patients for mastopexy-augmentation, and 90 patients for mastopexy. Only primary surgeries that had a full year follow-up comparing preoperative and postoperative measurements were reviewed. Measurements were performed by E.H.F. preoperatively and at each postoperative visit. The measurements that were included in this study were clavicle to upper breast border, upper breast border to nipple, suprasternal notch to nipple, suprasternal notch to inframammary fold, and midline to nipple.

Results
The preoperative and postoperative measurement changes in aesthetic breast surgery were consistent, with minimal variation for each of the aesthetic breast surgery procedures.

Conclusions
The visual interpretation of these results allows the surgeon to accurately plan preoperatively to achieve good, predictable results.
The non-specific lethal complex regulates genes and pathways genetically linked to Parkinson’s disease
Authors: Hicks Amy R , Reynolds Regina H , O’Callaghan Benjamin , García-Ruiz Sonia , Gil-Martínez Ana Luisa , Botía Juan , Plun-Favreau Hélène , Ryten Mina 
Published: July 2023

Abstract
Genetic variants conferring risks for Parkinson’s disease have been highlighted through genome-wide association studies, yet exploration of their specific disease mechanisms is lacking. Two Parkinson’s disease candidate genes, KAT8 and KANSL1, identified through genome-wide studies and a PINK1-mitophagy screen, encode part of the histone acetylating non-specific lethal complex. This complex localizes to the nucleus, where it plays a role in transcriptional activation, and to mitochondria, where it has been suggested to have a role in mitochondrial transcription. In this study, we sought to identify whether the non-specific lethal complex has potential regulatory relationships with other genes associated with Parkinson’s disease in human brain.
Correlation in the expression of non-specific lethal genes and Parkinson’s disease-associated genes was investigated in primary gene co-expression networks using publicly-available transcriptomic data from multiple brain regions (provided by the Genotype-Tissue Expression Consortium and UK Brain Expression Consortium), whilst secondary networks were used to examine cell type specificity. Reverse engineering of gene regulatory networks generated regulons of the complex, which were tested for heritability using stratified linkage disequilibrium score regression. Prioritized gene targets were then validated in vitro using a QuantiGene multiplex assay and publicly-available chromatin immunoprecipitation-sequencing data.
Significant clustering of non-specific lethal genes was revealed alongside Parkinson’s disease-associated genes in frontal cortex primary co-expression modules, amongst other brain regions. Both primary and secondary co-expression modules containing these genes were enriched for mainly neuronal cell types. Regulons of the complex contained Parkinson’s disease-associated genes and were enriched for biological pathways genetically linked to disease. When examined in a neuroblastoma cell line, 41% of prioritized gene targets showed significant changes in mRNA expression following KANSL1 or KAT8 perturbation. KANSL1 and H4K8 chromatin immunoprecipitation-sequencing data demonstrated non-specific lethal complex activity at many of these genes.
In conclusion, genes encoding the non-specific lethal complex are highly correlated with and regulate genes associated with Parkinson’s disease. Overall, these findings reveal a potentially wider role for this protein complex in regulating genes and pathways implicated in Parkinson’s disease.