bluuebunny/crossref_metadata_2025_split huggingface dataset:
A review of optic disc and optic cup segmentation based on fundus images
Authors: Ma Xiaoyue , Cao Guiqun , Chen Yuanyuan 
Published: May 2024

AbstractOptic disc (OD) and optic cup (OC) segmentation is an important task in ophthalmic medicine and is crucial for aiding glaucoma screening. With the development of smart healthcare and the increase of large datasets, there is an increasing number of research efforts targeting OD and OC segmentation, making it particularly important to provide a systematic review of the latest advances in the field. This paper presents a systematic review of commonly used datasets, evaluation metrics, and related research results in the field of OD and OC segmentation. The advantages and disadvantages of segmentation techniques based on traditional and deep learning methods are comparatively analysed. In addition, this study emphasizes the importance of OD and OC segmentation efforts in smart healthcare. Despite the technological advances, the lack of generalization capability is still a major obstacle limiting its clinical application. To address this issue, this study explores unsupervised domain adaptation methods to enhance the generalization performance of segmentation techniques and provide new strategies for clinical diagnosis. Finally, this paper discusses the challenges and future research directions faced by OD and OC segmentation when applied in the medical field to help readers comprehensively grasp the research dynamics in this area.
Pressure-Induced Distinct Self-Trapped Exciton Emission in Sb3+-Doped Cs2NaInCl6 Double Perovskite
Authors: Feng 冯 Youjia 友佳 , Chen 陈 Yaping 亚平 , Wang 王 Leyao 乐瑶 , Wang 王 Jiaxiang 家祥 , Chang 常 Duanhua 断华 , Yuan 袁 Yifang 亦方 , Wu 武 Min 敏 , Fu 付 Ruijing 瑞净 , Zhang 张 Lili 丽丽 , Wang 王 Qinglin 庆林 , Wang 王 Kai 凯 , Guo 郭 Haizhong 海中 , Wang 王 Lingrui 玲瑞 
Published: May 2024

Abstract
The Cs2NaInCl6 double perovskite is one of the most promising lead-free perovskites due to its exceptional stability and straightforward synthesis. However, it faces challenges related to inefficient photoluminescence. Doping and high pressure are employed to tailor the optical properties of Cs2NaInCl6. Herein, Sb3+ doped Cs2NaInCl6 (Sb3+:Cs2NaInCl6) was synthesized and it exhibits blue emission with a photoluminescence quantum yield of up to 37.3%. Further, by employing pressure tuning, a blue stable emission under a very wide range from 2.7 GPa to 9.8 GPa is realized in Sb3+:Cs2NaInCl6. Subsequently, the emission intensity of Sb3+:Cs2NaInCl6 experiences a significant increase (3.3 times) at 19.0 GPa. It is revealed that the pressure-induced distinct emissions can be attributed to the carrier self-trapping and detrapping between Cs2NaInCl6 and Sb3+. Notably, the lattice compression in the cubic phase inevitably modifies the band gap of Sb3+:Cs2NaInCl6. Our findings provide valuable insights into effects of the high pressure in further boosting unique emission characteristics but also offer promising opportunities for development of doped double perovskites with enhanced optical functionalities.
Enhancing automated inspection in metal industries: zero-shot segmentation of surface defects using bounding box prompts
Authors: Lema Darío G , Usamentiaga Rubén , García Daniel F 
Published: May 2024

AbstractSurface defect detection poses a challenging problem that has been addressed for decades. Many of actual solutions are based on deep learning algorithms. However, these algorithms require a large amount of data to train accurate models. This becomes especially problematic for semantic segmentation algorithms, which need labeled datasets at the pixel level, a laborious and time-consuming task. Therefore, this paper proposes a semi-supervised method in which the predictions of an object detector are combined with the segmentation of a zero-shot model, eliminating the need to label a dataset for semantic segmentation. Results are compared with relevant supervised semantic segmentation models, such as UNet and DeepLabv3+. UNet achieves an F1 score of 0.824, while DeepLabv3+ achieves 0.847. The proposed method combining YOLOv8n and Segment Anything Model achieves an F1 score of 0.804. This slight loss of F1 is compensated by the significant time savings, unlike UNet and DeepLabv3+, where labeling of the dataset is necessary.
Thermally compensated common-path differential interferometer with reduced long-term zero-drifts
Authors: Rerucha Simon , Hola Miroslava , Oulehla Jindrich , Lazar Josef , Mikel Bretislav , Cip Ondrej 
Published: May 2024

AbstractLaser interferometers have served as the workhorses in the metrology of length for several decades. Their broader application brings further challenges, especially for longer measurement time-frames or outside the laboratory environment with strictly controlled conditions. As a part of our team’s activities aiming at characterizing and eliminating the effects of unstable temperature on interferometric length measurements, we report on successfully remodelling a differential interferometer’s optical arrangement focused on increasing resilience against temperature changes. The experimental characterization under constant temperature and subsequently under thermal load proved a tenfold decrease in short-term fluctuations and reduced sensitivity to temperature changes by a factor of 100.
Erosion depth prediction of chloride ions under stray current using FEM based CNNs
Authors: Li Yu , Zhang Yishuang , Liu Gang , Li Zihao , Zhao Danyang , Xu Wenqiang , Qiang Sheng , Lai Jiayue 
Published: May 2024

Abstract
Stray currents can accelerate the transport of corrosive ions, especially Cl−, in concrete materials, which is very detrimental to structural safety. Effectively predicting the erosion depth of Cl− is crucial for evaluating structural safety. This article is based on a finite element model and verifies the erosion depth of Cl− under different voltages, Cl− concentrations, and corrosion time through experimental data. A polynomial was used to fit the quantitative relationship between erosion depth, Cl− concentrations, and corrosion time under single voltage condition. However, this formula only applies to a single voltage and has too many parameters. Therefore, this article also established a CNNs regression model to predict the depth of Cl−, and the results showed the multiple regression ability of CNNs. It has been proven that CNNs can accurately predict the erosion depth, which helps to accurately evaluate structural safety. After comparing experimental values, CNNs, ResNet, and ResNet-attention, it was found that residual networks and attention mechanisms did not significantly improve the prediction accuracy of deep networks, which may be related to insufficient data volume. After expanding the dataset, ResNet performed the best overall, and ResNet-attention had better testing performance, which is related to the powerful feature extraction ability of the attention mechanism.
Optimization of femtosecond laser processing parameters of SiC using ANN-NSGA-II
Authors: Li Chen , Ren Wanzhou , Wang Jing 
Published: May 2024

Abstract
In the field of femtosecond laser machining, it is essential to select the appropriate process parameters to obtain near thermal damage-free and high efficient machining of SiC wafer. In this work, a method of process parameter optimization for femtosecond laser machining of 4H–SiC was proposed by using the predictive ability of the Artificial Neural Network (ANN) and the optimization algorithm of the non-dominated sorting genetic algorithm (NSGA-II). Firstly, the femtosecond laser was used to fabricate microgrooves on SiC wafers, and the effects of process parameters (laser average power, scanning speed and repetition rate) on groove depth, width, heat affected zone and material removal rate were investigated. Secondly, the ANN model is established based on experimental data. Other experiments verify the accuracy of the model, and the average error in the model’s predictions is around 5%. Thirdly, Pareto optimal solutions are obtained by global optimization of the ANN model using the NSGA-II. The experimental results show that the Pareto optimal solutions are effective and reliable. This proposed method offers dependable guidance for the selecting and optimizing process parameters of high hardness and brittle materials in the field of femtosecond laser processing, and reduces the cost of selecting the appropriate processing parameters in the production process. The method can also be extended to other machining means, such as turning and milling.
Critical intermittency in rational maps
Authors: Jan Homburg Ale , Peters Han , Rabodonandrianandraina Vahatra 
Published: May 2024

Abstract
Intermittent dynamics is characterized by long periods of different types of dynamical characteristics, for instance almost periodic dynamics alternated by chaotic dynamics. Critical intermittency is intermittent dynamics that can occur in iterated function systems, and involves a superattracting periodic orbit. This paper will provide and study examples of iterated function systems by two rational maps on the Riemann sphere that give rise to critical intermittency. The main ingredient for this is a superattracting fixed point for one map that is mapped onto a common repelling fixed point by the other map. We include a study of topological properties such as topological transitivity.
Evaluation of an automated clinical decision system with deep learning dose prediction and NTCP model for prostate cancer proton therapy
Authors: Chen Mei , Pang Bo , Zeng Yiling , Xu Cheng , Chen Jiayi , Yang Kunyu , Chang Yu , Yang Zhiyong 
Published: May 2024

Abstract

Objective. To evaluate the feasibility of using a deep learning dose prediction approach to identify patients who could benefit most from proton therapy based on the normal tissue complication probability (NTCP) model. Approach. Two 3D UNets were established to predict photon and proton doses. A dataset of 95 patients with localized prostate cancer was randomly partitioned into 55, 10, and 30 for training, validation, and testing, respectively. We selected NTCP models for late rectum bleeding and acute urinary urgency of grade 2 or higher to quantify the benefit of proton therapy. Propagated uncertainties of predicted ΔNTCPs resulting from the dose prediction errors were calculated. Patient selection accuracies for a single endpoint and a composite evaluation were assessed under different ΔNTCP thresholds. Main results. Our deep learning-based dose prediction technique can reduce the time spent on plan comparison from approximately 2 days to as little as 5 seconds. The expanded uncertainty of predicted ΔNTCPs for rectum and bladder endpoints propagated from the dose prediction error were 0.0042 and 0.0016, respectively, which is less than one-third of the acceptable tolerance. The averaged selection accuracies for rectum bleeding, urinary urgency, and composite evaluation were 90%, 93.5%, and 93.5%, respectively. Significance. Our study demonstrates that deep learning dose prediction and NTCP evaluation scheme could distinguish the NTCP differences between photon and proton treatment modalities. In addition, the dose prediction uncertainty does not significantly influence the decision accuracy of NTCP-based patient selection for proton therapy. Therefore, automated deep learning dose prediction and NTCP evaluation schemes can potentially be used to screen large patient populations and to avoid unnecessary delays in the start of prostate cancer radiotherapy in the future.
Multiple skin transitions in two-band non-Hermitian systems with long-range nonreciprocal hopping
Authors: Li Ye-Wei-Yi , Nie Xiao-Feng , Cui Wen-Xue , Wang Hong-Fu 
Published: May 2024

Abstract
Non-Hermitian skin effect (NHSE) is a prominent feature in non-Hermitian physics, leading to novel topological properties and expanding the traditional energy band theories. In this paper, we investigate a two-band non-Hermitian system in which multiple skin transitions are induced by long-range nonreciprocal hopping. The spectral winding number under periodic boundary conditions reveals the localization directions of skin states. Further, we present the analytical solution of transition points by tracing the self-intersecting points on the complex plane. Interestingly, the current system exhibits the abundant NHSEs, including the normal, W-shaped, and bipolar localization properties, which the eigenstate distributions and the generalized Brillouin zone can clearly illustrate. We also provide a phase diagram to represent the skin transition properties of the system comprehensively. Further, we demonstrate that the multimer non-Hermitian lattices also present the anomalous skin effect and multiple transitions, which occur in the region of the bulk band touching, the same as the two-band lattice. Moreover, a feasible scheme is proposed to realize the current non-Hermitian system with long-range nonreciprocal hopping by a topoelectrical circuit. This work further supplies the content of skin transitions and may help us explore more plentiful localization features in the two-band non-Hermitian systems.
The magnetic coherent mode with shifted Alfvén gap frequency destabilized by the thermal trapped electron resonance in the pedestal of high-confinement tokamak plasmas
Authors: Wu (伍兴权) Xingquan , Xu (徐国盛) Guosheng , Chen (陈冉) Ran , Wan (万宝年) Baonian 
Published: May 2024

Abstract
The magnetic coherent modes (MCM) with toroidal mode number n about 1 (Chen R. et al 2018 Nucl. Fusion
58 112004) frequently appear in the edge pedestal of high-confinement tokamak plasmas on EAST in the absence of energetic particles. Although these modes are experimentally compatible with the steady-state operation of the pedestal, the driving mechanism without energetic particles of MCM is a long-standing mystery. To reveal the excitation mechanism, a fluid-drift kinetic hybrid local linear model has been developed. It is found that MCM is a new Alfvén eigenmode with a gap frequency much lower than the ideal Toroidal Alfvén Eigenmodes (TAEs) with two significant properties: (1) due to the unique steep pressure gradient in the pedestal region, the diamagnetic frequency becomes comparable to the ideal TAE frequency, which makes the Alfvén continuum in this region move significantly in the ion diamagnetic direction and form a gap of lower frequency; (2) due to the bounce frequencies of thermal electrons becoming also comparable to the ideal TAE frequency in the pedestal region, the free energy of the pressure gradient can be fed into the MCM through the thermal electron bounce resonance excitation, which is essentially the coupling between the shifted TAEs and low-

n

trapped electron modes. The low-

n

MCM is proved to be a shifted Alfvén gap mode in the pedestal region, which is anticipated to exist in low collisional plasmas of future fusion reactors. It is of great significance to carry out relevant physical model research to enhance the understanding of pedestal physics.
The impact of future UK offshore wind farm distribution and climate change on generation performance and variability
Authors: Giddings Josh , Bloomfield Hannah , James Rachel , Blair Michael 
Published: May 2024

Abstract
The UK plans to significantly increase offshore wind generation capacity as part of the effort to achieve net zero targets. Current installation is densely located in a few areas, particularly off the east coast of England, and although current siting proposals include new offshore regions, significant volumes of wind generation capacity are yet to be located to meet 2050 installation targets. This paper uses a recent dataset of multi-decadal offshore wind power capacity factor timeseries to assess how UK offshore wind generation is likely to be affected by both the spatial distribution of future wind farms, and by the impacts of near-future (2020–2050) climate change. We determine that a wider geographic spread of offshore capacity results in a much-improved and less-variable UK-aggregated power generation profile, with substantial reductions in periods of low generation and extreme wind power ramping events, without negatively impacting mean or peak generation outputs. The impact of near-term climate change appears to be minor, slightly reducing overall generation and possibly resulting in an underestimation of future installation requirements, but this climate signal is outweighed by the effects of spatial distribution, and even more so by inherent hourly to inter-annual wind speed variability. This study implies that the intermittency of wind generation can be partly mitigated through increasing the spatial diversity of the existing wind farm distribution. Alongside a more in depth investigation of future climate change, and a holistic assessment of relevant geospatial factors such as Levelised Cost of Energy, infrastructure, and environmental constraints, this study could be used for optimisation of future offshore wind siting.
Exhaled breath analysis in patients with potentially curative lung cancer undergoing surgery: a longitudinal study
Authors: Herth Jonas , Schmidt Felix , Basler Sarah , Sievi Noriane A , Kohler Malcolm 
Published: May 2024

Abstract
Exhaled breath analysis has emerged as a non-invasive and promising method for early detection of lung cancer, offering a novel approach for diagnosis through the identification of specific biomarkers present in a patient’s breath. For this longitudinal study, 29 treatment-naive patients with lung cancer were evaluated before and after surgery. Secondary electrospray ionization high-resolution mass spectrometry was used for exhaled breath analysis. Volatile organic compounds with absolute log2 fold change ⩾1 and q-values ⩾ 0.71 were selected as potentially relevant. Exhaled breath analysis resulted in a total of 3482 features. 515 features showed a substantial difference before and after surgery. The small sample size generated a false positive rate of 0.71, therefore, around 154 of these 515 features were expected to be true changes. Biological identification of the features with the highest consistency (m/z −242.18428 and m/z −117.0539) revealed to potentially be 3-Oxotetradecanoic acid and Indole, respectively. Principal component analysis revealed a primary cluster of patients with a recurrent lung cancer, which remained undetected in the initial diagnostic and surgical procedures. The change of exhaled breath patterns after surgery in lung cancer emphasizes the potential for lung cancer screening and detection.
Simple two-step synthesis of Ag/ZnO nanoparticles with enhanced photocatalytic response
Authors: Flores-Castañeda Mariela , Meza Lilibeth , Guevara-Martínez Santiago José , Pérez-Centeno A , Quiñones-Galván J G 
Published: May 2024

Abstract
This study presents a simple two-step synthesis method for the fabrication of Ag/ZnO nanocomposites to improve the photocatalytic response of ZnO. The synthesis involves ZnO nanoparticles that were fabricated from the thermal decomposition of commercial zinc acetate. In order to produce Ag/ZnO nanoparticles in a simple two-step process, ZnO nanoparticles were mixed with Ag nanoparticle suspensions previously obtained by the laser ablation of solids in liquids technique at three different fluences. Structural characterization of ZnO powders revealed the presence of single phase wurtzite ZnO nanoparticles with crystal sizes of 20 nm. On the other hand, XRD patterns for a composite sample revealed the presence of signals associated to both ZnO and Ag suggesting that silver nanoparticles were attached to the ZnO particles surface. Optical characterization of the ZnO powders, carried out by UV–vis spectroscopy, showed a strong absorption band centered at 380 nm, which is associated to excitonic transitions in ZnO nanoparticles, whilst absorption measurements of silver nanoparticles colloids revealed the presence of a strong band centered near 412 nm. This band shifts to shorter wavelengths with increasing fluence from 2.6 to 6.2 J cm−2, indicating changes in nanoparticles size. Photocatalytic degradation tests of methylene blue under UV irradiation were carried out using pure ZnO, Ag colloids and Ag/ZnO nanoparticles. After the first 30 min of irradiation, it was observed that the silver nanoparticles reached degradation percentages of 16, 22 and 29% for samples synthesized at 2.6, 4.2 and 6.2 J cm−2, respectively. Meanwhile the ZnO sample reached a value of 13% after 30 min. Regarding the Ag/ZnO composite sample, the percentage of degradation after 30 min was 36%, demonstrating a considerable enhanced photocatalytic activity as compared to ZnO. After 24 h irradiation, Ag/ZnO degraded 95% of the methylene blue solution. It was observed that decorating ZnO with laser produced silver nanoparticles accelerates the photocatalytic response of ZnO by enhancing the activity at short times.
Investigating the Z-scan technique for quantifying circulating cell-free DNA (ccfDNA) extracted from blood plasma as a potential biomarker for various cancers
Authors: Ara H , Tarek S A , Biswas M K , Al-Din S M S , Hoque E , Hasan K M E , Hossain A K M M , Faruque S B , Haque Y , Sharafuddin S M 
Published: May 2024

Abstract
The Z-scan technique is a nonlinear optical method that has found applications in characterizing various materials, particularly those exhibiting nonlinear optical response (NLOR). This study applies the continuous wave (CW) Z-scan technique to examine the NLOR in terms of the nonlinear optical phase shifts

(
Δ

Φ

0

) exhibited by the ccfDNA extracted from blood plasma samples collected from a group constituting 30 cancer-diagnosed patients and another group constituting 30 non-diagnosed individuals. The cancer group exhibited significantly higher

Δ

Φ

0

versus incident power slopes compared to the non-cancer group (0.34 versus 0.12) providing a clear distinction between the two groups. The receiver operating characteristic (ROC) curve analysis of the results indicates a clear separation between cancer and non-cancer groups, along with a 94% accuracy rate of the data. The Z-scan results are corroborated by spectrophotometric analysis, revealing a consistent trend in the concentration values of ccfDNA samples extracted from both cancerous and non-cancerous samples, measuring 3.24 and 1.41 respectively. Additionally, more sensitive fluorometric analyses of the respective samples demonstrate significantly higher concentrations of ccfDNA in the cancer group, further affirming the correlation with the Z-scan results. The study suggests that the Z-scan technique holds promise as an effective method for cancer detection, potentially contributing to improved oncology diagnosis and prognosis in the future.
An approach to calculate Franck-Condon factors involving anharmonic potentials using harmonic oscillator bases
Authors: Suárez E , Lemus R 
Published: May 2024

Abstract
In this contribution a discrete variable representation (DVR) approach to calculate Franck-Condon factors (FCFs) is presented. The method is illustrated using a harmonic oscillator basis. The advantage of this approach is that it is possible to calculate FCFs associated with general potentials based on the knowledge of the harmonic oscillator theory. First the coordinate and momentum representations are introduced. Based on this concept, the DVR is proposed, which allows the Franck-Condon factors to be calculated in a simple form. This method takes advantage of the momentum as generator of translations to include the displacement of the potentials. The calculation of the FCFs is exemplified for transitions involving the ground state

X

1

Σ

g

+

and the excited state a
1Π
g
of the diatomic molecule 14N2 both modelled with Morse potentials.