bluuebunny/crossref_metadata_2025_split huggingface dataset:
Vector dark–bright pulses from a ytterbium doped fiber laser mode-locked by nonlinear multimode interference
Authors: Gupta Pradeep K , Singh C P , Mukhopadhyay P K , Dixit S K , Bindra K S 
Published: March 2023

Abstract
We report dark–bright pulse pair generation from the ytterbium doped fiber laser mode-locked by cascaded nonlinear multimode interference (MMI) effect under an all-normal dispersion configuration. The MMI is implemented in a step index single mode–multimode–single mode fiber structure. The combination of two MMI structures, acting like a saturable absorber, has been used for stable mode-locking operation in the resonator. By adjusting the polarization controller attached to one of the MMI structure, stable dark–bright pulses are observed at fundamental, second and third harmonic repetition rates. The optical spectrum of the dark–bright pulses is doubly peaked at 1036.6 and 1040.6 nm with a spectral width ∼0.7 nm. The width of the dark pulses varied from 72 to 50 ns and that of the bright pulses from 30 to 14 ns when the pump power is increased from 102 to 170 mW at the fundamental repetition rate mode-locking. The darkness of the dark and intensity of bright pulses increase with the pump power. Dark and bright pulses in the pair are resolved by placing a polarizing component confirming their vector nature.
The Stellar Spectra Factory (SSF) Based on SLAM
Authors: Ji Wei , Liu Chao , Zhang Bo 
Published: March 2023

Abstract
An empirical stellar spectral library with large coverage of stellar parameters is essential for stellar population synthesis and studies of stellar evolution. In this work, we present Stellar Spectra Factory (SSF), a tool to generate empirical-based stellar spectra from arbitrary stellar atmospheric parameters. The relative flux-calibrated empirical spectra can be predicted by SSF given arbitrary effective temperature, surface gravity, and metallicity. SSF constructs the interpolation approach based on the Stellar LAbel Machine, using ATLAS-A library, which contains spectra covering from O type to M type, as the training data set. SSF is composed of four data-driven sub-models to predict empirical stellar spectra. Sub-model SSF-N can generate spectra from A to K type and some M giant stars, covering 3700 < T
eff < 8700 K, 0 <

log
g

< dex, and −1.5 < [M/H] < 0.5 dex. Sub-model SSF-gM is mainly used to predict M giant spectra with 3520 < T
eff < 4000 K and −1.5 < [M/H] < 0.4 dex. Sub-model SSF-dM is for generating M dwarf spectra with 3295 < T
eff < 4040 K, −1.0 < [M/H] < 0.1 dex. Sub-model SSF-B can predict B-type spectra with 9000 < T
eff < 24,000 K and −5.2 < M

G
< 1.5 mag. The accuracy of the predicted spectra is validated by comparing the flux of predicted spectra to those with same stellar parameters selected from the known spectral libraries, MILES and MaStar. The averaged difference of flux over optical wavelength between the predicted spectra and the corresponding ones in MILES and MaStar is less than 5%. More verification is conducted between the magnitudes calculated from the integration of the predicted spectra and the observations in PS1 and APASS bands with the same stellar parameters. No significant systematic difference is found between the predicted spectra and the photometric observations. The uncertainty is 0.08 mag in the r band for SSF-gM when comparing with the stars with the same stellar parameters selected from PS1. The uncertainty becomes 0.31 mag in the i band for SSF-dM when comparing with the stars with the same stellar parameters selected from APASS.
A high-intensity superconducting H+
3 cyclotron for isotope production
Authors: Rao Y.-N. , Zhang L.G. , Baartman R. , Bylinskii Y. , Koay H.W. , Planche T. 
Published: March 2023

Abstract
We're concerned with future accelerators of high intensity
protons for isotope production. To this end, we initiate a proposal
to design an innovative superconducting H+
3 cyclotron TR150,
aiming at proton energy of 70–150 MeV and proton current
of ∼ 1.0 mA. Cyclotrons in this energy range are not developed
world-wide; moreover numerous highly interesting and increasingly
demanded radio­nuclides are in this energy range. Our machine shall
be designed to accelerate H+
3 ion, the simplest and stable
triatomic molecular ion, by injection from an external ion source
and extraction by stripping. This has potential to extract proton
beam of variable energies with very high extraction efficiency, and
thus enables to simultaneously provide multiple proton beams for
multiple external production targets. A baseline design of our
machine and the beam dynamics studies are presented in this paper.
Beam dynamics and space charge studies for the InnovaTron cyclotron
Authors: D'Agostino G. , Kleeven W. 
Published: March 2023

Abstract
At IBA a high-intensity compact self-extracting cyclotron is
being studied. There is no dedicated extraction device but instead,
a special shaping of the magnetic iron and the use of harmonic coils
to create large turn-separation. Proton currents up to 5 mA are
aimed for. This would open new ways for large-scale production of
medical radioisotopes. The main features of the cyclotron are
presented. A major variable of the beam simulations is the space
charge effect in the cyclotron centre. Using the SCALA-solver of
Opera3D, we attempt to find the ion source plasma meniscus and the
beam phase space and current extracted from it. With these
properties known, we study the bunch formation and acceleration
under high space charge condition with our in-house tracking code
AOC. We also discuss a new tool that automates optimization of
cyclotron settings for maximizing beam properties such as extraction
efficiency.
Cyclotron beam extraction by acceleration
Authors: Baumgarten C. 
Published: March 2023

Abstract
One of the decisive issues in the design and operation of
cyclotrons is the choice of the beam extraction method. Typical
methods are extraction by electrostatic extractors and by
stripping. The former method requires DC high voltage electrodes
which are notorious for high-voltage breakdowns. The latter method
requires beams of atomic or molecular ions which are notorious for
rest gas and Lorentz stripping. Here we discuss the conditions to
be met such that a beam will leave the magnetic field of an
isochronous cyclotron purely by fast acceleration.
Electronic frustration, Berry’s phase interference and slow dynamics in some tight-binding systems coupled to harmonic baths
Authors: Makri Nancy 
Published: March 2023

Abstract
Conical intersections in two-state systems require a coordinate-dependent coupling. This paper identifies and investigates conical intersections in cyclic tight-binding system-bath Hamiltonians with an odd number of sites and a constant site-to-site coupling. In the absence of bath degrees of freedom, such tight-binding systems with a positive coupling parameter exhibit electronic frustration and a doubly-degenerate ground state. When these systems interact with a harmonic bath, the degeneracy becomes a conical intersection between the adiabatic ground and first excited states. Under weak system-bath coupling, overlapping wavefunctions associated with different sites give rise to distinct pathways with interfering geometric phases, which lead to considerably slower transfer dynamics. The effect is most pronounced in the presence of low-temperature dissipative baths characterized by a continuous spectral density. It is found that the transfer dynamics and equilibration time of a cyclic dissipative three-site system with a positive coupling exceeds that of a similar three-site system with a negative coupling, as well as that of cyclic four-site systems, by an order of magnitude.
Characterization and filtering of profile and areal surface topography by combining the discrete Legendre and cosine transforms
Authors: Haitjema Han 
Published: March 2023

Abstract
In the standardized processing of surface topography data, the form removal and filtering operations are clearly separated. This is reflected in the current ISO standards concerning profile surface texture and areal surface texture, the ISO 21920 and the ISO 25178 series respectively. When the scale-limited surface texture is significant compared to the form to be removed, for example with additive manufactured surfaces, the dependence of the surface Fourier spectrum on the removed form and orientation may become significant. This may lead to interaction between the form removal and filtering operations. To counter this interaction, in this paper, the lower-order discrete Legendre polynomials that describe the form are combined with cosine functions that describe the surface texture. This set of base functions is orthonormalized using a Gram-Schmidt procedure. This results in a set of orthonormal functions that allow an independent parameterization of both form and texture. The concept and the related theory are given and illustrated using examples of filtering profiles and areal topographies, description of cylinders and treatment of missing data. The examples show that the concept as presented in this paper is useful for filtering surfaces with a dominant form and can be used in the parametrization of surfaces and cylindrical geometries. Also, the methods presented here can be used for filtering and parametrization in the case of missing points in the data, actual holes in the profile or non-rectangular surfaces.
Photothermal ultra-high molecular weight polyethylene/MXene aerogel for crude oil adsorption and water evaporation
Authors: Zhang Mingtao , Su Meng , Qin Yijing , Liu Chuntai , Shen Changyu , Ma Jun , Liu Xianhu 
Published: March 2023

Abstract
The frequent oil spill accidents during oil exploration and transportation have caused large economic loss and catastrophic environmental disasters. Due to low cost and simplicity, adsorption and filtration materials are often chosen to deal with oil spills, but the outcomes are not satisfactory mainly because of the awfully high viscosity of crude oil. Herein a photothermal ultra-high molecular weight polyethylene/MXene composite aerogel with a high light absorption (99.97%) and water repellency (water contact angle >148°) is developed by thermally induced phase separation method. The composite aerogel endows durable hydrophobicity with which the water contact angle is more than 142° in acidic/alkaline environments, and the maximum absorption capacity of 81 g g−1. In addition, it exhibits an excellent photothermal performance, rising surface temperature to 70 °C within 60 s under 1 sun irradiation, that can drastically reduce the crude oil absorption time from 60 min to 60 s, saving 98% of absorption time and reaching a crude oil absorption capacity of 21 g g−1. More interestingly, the designed solar evaporation device with the obtained composite aerogel can achieve an evaporation rate of 1.15 kg m−2h−1 and evaporation efficiency of 74%. The designed composite aerogel opens a possible pathway for solar-powered crude oil adsorption applications.
Investigation of the J-TEXT plasma events by k-means clustering algorithm
Authors: LI Jianchao , ZHANG Xiaoqing , ZHANG Yu , BALA Abba Alhaji , LIU Huiping , ZHOU Guohong , WANG Nengchao , LI Da , CHEN Zhongyong , YANG Zhoujun , CHEN Zhipeng , DONG Jiaolong , DING Yonghua 
Published: March 2023

Abstract
Various types of plasma events emerge in specific parameter ranges and exhibit similar characteristics in diagnostic signals, which can be applied to identify these events. A semi-supervised machine learning algorithm, the k-means clustering algorithm, is utilized to investigate and identify plasma events in the J-TEXT plasma. This method can cluster diverse plasma events with homogeneous features, and then these events can be identified if given few manually labeled examples based on physical understanding. A survey of clustered events reveals that the k-means algorithm can make plasma events (rotating tearing mode, sawtooth oscillations, and locked mode) gathering in Euclidean space composed of multi-dimensional diagnostic data, like soft x-ray emission intensity, edge toroidal rotation velocity, the Mirnov signal amplitude and so on. Based on the cluster analysis results, an approximate analytical model is proposed to rapidly identify plasma events in the J-TEXT plasma. The cluster analysis method is conducive to data markers of massive diagnostic data.
Global modeling of SDG indicators related to small-scale farmers: testing in a changing climate
Authors: Nozaki Noriko , Hosokawa Nanae , Doi Yasuhiro , Kim Wonsik , Iizumi Toshichika 
Published: March 2023

Abstract
Some indicators used to track the progress of the Sustainable Development Goals (SDGs) suffer from a lack of reported data, and therefore need estimates to fill the data gaps. Using crop model outputs and global cropping system datasets, we present a modeling of small-scale farmer productivity and agricultural output (conceptually similar to the formal SDG 2.3.1 and 2.3.2 indicator, respectively). We analyze the responses of the indicators for 106 low- and middle-income countries for the periods 2051–2060 and 2091–2100, relative to 2001–2010, to various scenarios of climate, socioeconomic development, cost-free adaptation, and irrigation expansion. The results show the potentials of modeling in gap-filling of reported national data, and that the agricultural output indicator indicates the positive effect of climate mitigation to small-scale farmers. The contributions of adaptation are evident when agricultural output indicator is used but are no longer visible, or even wrongly interpreted, when productivity indicator is used, underling the importance of selecting robust indicators to track SDG goals in a changing climate. Also discussed are the caveats identified in the SDG 2.3 indicators that enable the design of indicators more aligned with the other development goals, such as poverty eradication.
On the role of local and large-scale atmospheric variability in snow cover duration: a case study of Montevergine Observatory (Southern Italy)
Authors: Annella Clizia , Budillon Giorgio , Capozzi Vincenzo 
Published: March 2023

Abstract
Snow cover plays an important role in Earth’s climate, hydrological and biological systems as well as in socio-economical dynamics, especially in mountain regions. The objective of this work is to provide the first evidence about snow cover variability in the Italian Southern Apennines and investigate the forcing mechanisms controlling it. To this purpose, we present a new historical long-term (from 1931 to 2008) series of snow cover duration data observed at Montevergine Observatory, a mountainous site located at 1280 m above sea level. From the analysis of this series, it emerged a strong interannual variability, an overall reduction over time of snow cover days until mid-1990s and a recovery in the last 10-years. We model snow cover duration employing a multiple linear regression, considering both local and large-scale climate factors as explanatory variables. Our findings show that snow cover duration appears to be primarily dependent on temperature, which exhibits a positive trend in the considered time interval. However, the interannual and decadal fluctuations of the examined parameter are also strongly modulated by two large-scale patterns, the Arctic Oscillation and the Eastern Mediterranean Pattern. In the last segment of the considered time interval, the increase in temperature is not consistent with the dominant patterns of large-scale indices, which proved to be more effective in capturing the recent rebound in snow cover duration. The results demonstrate that snow cover duration is linked to the global warming by a non-trivial relationship and that its behaviour, in specific periods, can be largely independent from rising temperature tendency, according to the prevailing phase of large-scale atmospheric patterns.
Using concentration gradients to examine the effects of Al, Ga and Sn additions on the low-activation VCrMnFe system
Authors: Carruthers A W , Shahmir H , Rigby M , Gandy A S , Pickering E J 
Published: March 2023

Abstract
A critical design criterion for future fusion reactor components is low activation. The equiatomic multi-principal element alloy VCrMnFe is comprised solely of low activation elements and forms a single-phase solid solution at temperatures over 1000 °C. However, at lower temperatures it forms detrimental sigma phase. In this work, compositional gradients of Ga, Sn or Al were induced in VCrMnFe using only a furnace to investigate their effect on intermetallic formation. By examining how the microstructure changed across a region with varying composition, phase stability limits could be assessed. For example, all three elements were found to prevent sigma phase from forming within the alloy when they were present at relatively low concentrations (2–5 at%). Al was found to be the most promising addition (in terms of not causing embrittlement), and the approach used enabled the characterisation of the VCrMnFe–Al pseudo binary phase diagram up to 50 at% Al after heat treatment of 800 °C/240 h followed by ageing at 600 °C/240 h, with numerous ordered phases found using electron diffraction. The level of Al addition required to suppress the sigma phase has been identified more precisely, which will be useful for future alloy development work.
An investigation on machinability of AISI D2 steel during hard milling with multi-resolution analysis of vibration
Authors: Chattopadhyay Arghya , Mandal Nirmal Kumar , Maity Arpan 
Published: March 2023

Abstract
Vibration is a major concern in hard milling process as it adversely affects productivity, surface finish, tool wear, energy consumption, etc. The aim of this paper is to investigate the effects of cutting parameters on acceleration of vibration, acoustic pressure, surface finish, and tool flank wear in face milling of AISI D2 steel. Each cutting parameter was varied in four levels while keeping the maximum value of the other two parameters as constant. Wavelet transform was used to decompose the signals of vibration. Acceleration of vibration has been found to rise with increasing cutting speed in the range of 100 to 180 m min−1. In general, acoustic pressure was found to increase with increasing depth of cut and cutting speed. The results showed that increasing cutting speed leads to reduction in surface roughness while feed rate and cutting depth have opposite effects. It was revealed that while flank wear increases with increasing depth of cut and feed rate, it reduces when cutting speed is raised in the range of 100 to 180 m min−1.
Prediction of the settlement associated with construction on soft clay improved using rigid inclusions considering the installation effect
Authors: Samy Marco , Abdelfattah Ali , Fayed Ayman , Sorour Tamer , Elshawaf Mahmoud 
Published: March 2023

Abstract
One of the most common methods in soil improvement of soft soils is using rigid inclusions (RI) that enhance the stiffness of the soil surrounding and beneath the inclusions. This paper aims to develop simple and user-friendly charts to estimate the settlement improvement factor (N) that correlates the settlement values without soil improvement to the settlement values after improvement, considering the installation effect of the rigid inclusions in soft clay formations. The cavity expansion method is used to model the installation process of the rigid inclusions. A parametric study is carried out using numerical modelling to predict the variation in the improvement factor with the variation of the treated soil stiffness and geometry of the RI system. The analyses are performed using a verified numerical model for a case study of a zone loading test performed at New Mansoura city in Egypt, employing the finite element software (PLAXIS 3D). The cavity expansion approach is first utilized for an axisymmetric model by imposing a prescribed displacement equivalent to the inclusion radius to simulate the construction effect of the rigid inclusion. From the axisymmetric model, the enhancement in the deformation modulus and the over consolidation ratio of the soft clay, resulting from the construction of the rigid inclusions, are determined. In the second stage of the analysis, the improved soil parameters are then implemented in the 3D finite element model, in which the external stresses due to superstructure are applied over the improved soil. The settlement associated with loading both the improved and unimproved soils is then compared for each studied condition in the parametric study to determine the improvement factor (N). The performed analyses clearly showed the high effect of the rigid inclusions in reducing the settlement associated with the construction on the improved soft clay. The achieved improvement factor varies between 2.88 to 58.10, with an average value of about 12.00. Based on the conducted parametric study, design charts are developed to provide a simple tool for predicting the settlement values associated with construction on improved soft clay formations with rigid inclusions under different conditions.
Fine-grained selective similarity integration for drug–target interaction prediction
Authors: Liu Bin , Wang Jin , Sun Kaiwei , Tsoumakas Grigorios 
Published: March 2023

AbstractThe discovery of drug–target interactions (DTIs) is a pivotal process in pharmaceutical development. Computational approaches are a promising and efficient alternative to tedious and costly wet-lab experiments for predicting novel DTIs from numerous candidates. Recently, with the availability of abundant heterogeneous biological information from diverse data sources, computational methods have been able to leverage multiple drug and target similarities to boost the performance of DTI prediction. Similarity integration is an effective and flexible strategy to extract crucial information across complementary similarity views, providing a compressed input for any similarity-based DTI prediction model. However, existing similarity integration methods filter and fuse similarities from a global perspective, neglecting the utility of similarity views for each drug and target. In this study, we propose a Fine-Grained Selective similarity integration approach, called FGS, which employs a local interaction consistency-based weight matrix to capture and exploit the importance of similarities at a finer granularity in both similarity selection and combination steps. We evaluate FGS on five DTI prediction datasets under various prediction settings. Experimental results show that our method not only outperforms similarity integration competitors with comparable computational costs, but also achieves better prediction performance than state-of-the-art DTI prediction approaches by collaborating with conventional base models. Furthermore, case studies on the analysis of similarity weights and on the verification of novel predictions confirm the practical ability of FGS.