bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quaternary functional semiconductor devices
Authors: Altındal Yerişkin S , Dere A , Orman Y , Yakuphanoğlu F 
Published: May 2024

Abstract
Al/(Zn:Cd:Ni:TiO2)/p-Si diodes with (4:2:2:2), (5:2:2:1) and (6:4:4:0) ratios were named as D1, D2, D3, and Al/(CdO:ZnO:NiO:Ti)/p-Si diodes with of (4:2:2:2), (5:2:2:1) and (6:4:4:0) ratios were named as D4, D5 and D6, respectively. The functional interlayer was deposited via sol-gel spin coating method to develop new diodes/structures. Whereas the Ln(I)–V plot shows two linear sections for D1, D2, D3, and D5 structures, D2 and D6 revealed only one linear section in the forward-bias voltages. Therefore, D1, D2, D3, and D5 structures were found to exhibit two-exponential or two-parallel diode behavior in literature. The main electric parameters such as zero-bias barrier height, BH, (Φbo), ideality factor (n), reverse saturation-current (Is or Io)), rectification ratio at ±4.5 V, series resistance (Rs) and shunt resistance (Rsh) were extracted from the current-voltage (I-V) measurements. The number of surface sates (Nss) and their energy distribution were obtained using forward-bias I-V data by considering the voltage dependence of n and Φbo for each diode. The capacitance/conductance-voltage (C/G–V) plots at 1 MHz were used for extracting some of the other basic electrical parameters. The comparison of all the experimental results suggests that D1 and D3 structures have good performance in terms of lower leakage current, Nss and higher RR and so could be successfully used instead of conventional metal/insulator/semiconductor (MIS) structures.
Effect of different surface alignment layers and temperature changes on bandwidth of Bragg reflection in chiral nematic liquid crystal
Authors: Khalil Sarbaz Ramin , Zakerhamidi Mohammadsadeg , Rezaei Behroz , Ranjkesh Amid 
Published: May 2024

Abstract
In recent years, the practical properties of cholesteric liquid crystals (CLCs) have been widely studied due to their unique feature of selective Bragg reflection. In this study, we investigated the following aspects: (i) the effect of surface alignment using polyvinyl alcohol, polyamide, and polyimide as covering substrate, (ii) the impact of temperature changes on the reflection bandwidth and, consequently, variations in the cholesteric pitch. Furthermore, we extended Li’s four-parameter model to the cholesteric environment using Haller’s assumption and Vuk’s equations for nematic liquid crystals (NLCs) and Fergason’s theory for CLCs. The fit of the experimental data with this model demonstrated an excellent agreement. The experimental data revealed that the S5011 chiral dopant, with left-handedness, used in the NLC environment of the host, exhibits a significant helical twist power (HTP). This leads to the narrowing of the reflection band width with increasing temperature, without causing a noticeable change in the wavelength of the central reflection. This feature highlights the high potential of these types of chiral materials as thermally stable materials for creating selective-reflective optical filters that remain stable with temperature changes, particularly away from the cholesteric to isotropic transition point.
High power single crystal KTA optical parametric amplifier for efficient 1.4–3.5 µm mid-IR radiation generation
Authors: Csanaková Bianka , Novák Ondřej , Roškot Lukáš , Mužík Jiří , Smrž Martin , Jelínková Helena , Mocek Tomáš 
Published: May 2024

Abstract
In this paper, we present a single crystal, KTA (potassium titanyl-arsenate, KTiOAsO4) based picosecond optical parametric amplifier pumped by an in-house built 1030 nm Yb:YAG thin-disk laser, capable of tunability from 1.46 to 3.5 µm, operating at 90 kHz, with high average power in the signal and idler beams. The highest output power of 8.9 W was reached for the 1750 nm signal beam with 19% conversion efficiency and the respective 2500 nm idler beam power was 6.2 W with 13% efficiency. The highest combined signal and idler mid-infrared power was 17 W at the 2060 nm wavelength degeneracy point.
EEG connectivity in functional brain networks supporting visuomotor integration processes in dominant and non-dominant hand movements
Authors: Calcagno Alessandra , Coelli Stefania , Corda Martina , Temporiti Federico , Gatti Roberto , Galli Manuela , Bianchi Anna Maria 
Published: May 2024

Abstract

Objective. This study explores the changes in the organization of functional brain networks induced by performing a visuomotor integration task, as revealed by noninvasive spontaneous electroencephalographic traces (EEG). Approach. EEG data were acquired during the execution of the Nine Hole Peg Test (NHPT) with the dominant and non-dominant hands in a group of 44 right-handed volunteers. Both spectral analysis and phase-based connectivity analysis were performed in the theta (ϑ), mu (

μ

) and beta (ß) bands. Graph Theoretical Analysis (GTA) was also performed to investigate the topological reorganization induced by motor task execution. Main results. Spectral analysis revealed an increase of frontoparietal ϑ power and a spatially diffused reduction of µ and ß contribution, regardless of the hand used. GTA showed a significant increase in network integration induced by movement performed with the dominant limb compared to baseline in the ϑ band. The µ and ß bands were associated with a reduction in network integration during the NHPT. In the µ rhythm, this result was more evident for the right-hand movement, while in the ß band, results did not show dependence on the laterality. Finally, correlation analysis highlighted an association between frequency-specific topology measures and task performance for both hands. Significance. Our results show that functional brain networks reorganize during visually guided movements in a frequency-dependent manner, differently depending on the hand used (dominant/non dominant).
A systematic evaluation of Euclidean alignment with deep learning for EEG decoding
Authors: Junqueira Bruna , Aristimunha Bruno , Chevallier Sylvain , de Camargo Raphael Y 
Published: May 2024

AbstractObjective:Electroencephalography signals are frequently used for various Brain–Computer interface (BCI) tasks. While deep learning (DL) techniques have shown promising results, they are hindered by the substantial data requirements. By leveraging data from multiple subjects, transfer learning enables more effective training of DL models. A technique that is gaining popularity is Euclidean alignment (EA) due to its ease of use, low computational complexity, and compatibility with DL models. However, few studies evaluate its impact on the training performance of shared and individual DL models. In this work, we systematically evaluate the effect of EA combined with DL for decoding BCI signals.Approach:We used EA as a pre-processing step to train shared DL models with data from multiple subjects and evaluated their transferability to new subjects.Main results:Our experimental results show that it improves decoding in the target subject by 4.33% and decreases convergence time by more than 70%. We also trained individual models for each subject to use as a majority-voting ensemble classifier. In this scenario, using EA improved the 3-model ensemble accuracy by 3.71%. However, when compared to the shared model with EA, the ensemble accuracy was 3.62% lower.Significance:EA succeeds in the task of improving transfer learning performance with DL models and, could be used as a standard pre-processing technique.
Stability analysis of plasma waves driven by runaway electrons in tokamak hot plasmas
Authors: Castaldo C. , Della Volpe L. , Fedele R. , Bin W. , Buratti P. , Cardinali A. , Napoli F. , Marinucci M. , Apruzzese G. , Cianfarani C. , Giovannozzi E. , Tudisco O. 
Published: May 2024

Abstract
The local stability analysis of plasma waves driven by runaway electrons (REs) has been performed considering hot plasma Maxwellian background, with electron and ion temperatures of the order of 1 keV. It is shown that hot plasma waves, namely electron plasma waves (EPWs) and ion Bernstein waves (IBWs) can be driven unstable by RE at their coalescence frequency via Cherenkov resonance by RE with energy distribution peaked at about 8 MeV. A skew-normal distribution is used as a model of the RE energy distribution. The EPW and IBW couples of waves occur between any successive ion-cyclotron harmonics frequencies nf
ci, above the lower hybrid resonance. At their confluence, the perpendicular group velocity vanishes and significant RF emissions are expected. The frequency gap between two successive confluences is ∼f
ci. Groups of RF line emissions, separated by almost constant frequency gap ∼f
ci/2 are detected during various quiescent runaway plasma discharges in the FTU tokamak. The analysis of a specific discharge suggests that the frequencies of the line emissions observed and the frequencies occurring at the EPW-IBW confluences are in reasonable agreement. A possible explanation of the line emissions with ∼f
ci/2 gap in terms of nonlinear mode coupling is proposed.
The status of the back-end card for the JUNO experiment
Authors: Gao Feng , Yang Yifan , Petitjean Pierre-Alexandre , Clerbaux Barbara , Colomer Molla Marta 
Published: May 2024

Abstract
The Jiangmen Underground Neutrino Observatory (JUNO) aims to determine the neutrino mass hierarchy by detecting antineutrinos from nuclear reactors using a large liquid scintillator volume. The detector employs approximately 20,000 20-inch photomultiplier tubes powered and read out by two electronics readout systems: underwater and above water. The back-end card (BEC) is a crucial component of the latter and links 7,000 underwater electronics boxes to the trigger system. 180 BECs have been installed and tested at the JUNO site, including self-tests and combined tests. This paper presents the current status of the BEC.
High intensity beam dynamics assessment and challenges for HL-LHC
Authors: Mounet N. , Tomás R. , Amorim D. , Antuono C. , Biancacci N. , Bartosik H. , Baudrenghien P. , Bruce R. , Buffat X. , Calaga R. , De Maria R. , Droin C. , Giacomel L. , Giovannozzi M. , Iadarola G. , Kostoglou S. , Kurtulus A. , Lindström B. , Mether L. , Métral E. , Papaphilippou Y. , Paraschou K. , Redaelli S. , Rumolo G. , Salvant B. , Sito L. , Sterbini G. , Zannini C. 
Published: May 2024

Abstract
The High Luminosity (HL-LHC) project aims to increase the
integrated luminosity of CERN's Large Hadron Collider (LHC) by an
order of magnitude compared to its initial design. This requires a
large increase in bunch intensity and beam brightness compared to
the first three LHC runs, and hence poses serious collective-effects
challenges, related in particular to electron cloud, instabilities
from beam-coupling impedance, and beam-beam effects. Here, we
present the associated constraints and the mitigation measures
proposed to achieve the baseline performance of the upgraded LHC
machine. We also discuss the interplay of these mitigation measures
with other aspects of the accelerator, such as optics, physical and
dynamic apertures, the collimation system, and crab
cavities. Additional potential sources of intensity limitations are
also briefly discussed.
Coupled dynamic modeling of scrap melting and gas phase reactions in the electric arc furnace process
Authors: Mäkelä I , Visuri V-V , Aula M , Echterhof T 
Published: May 2024

Abstract
Gas phase reactions have a significant effect on the composition and heat content of the off-gas in the electric arc furnace (EAF) process. In this work, a previously developed dynamic scrap melting and heat transfer model was coupled with a gas phase reaction module based on Gibbs energy minimization. The gas phase reaction module retrieves the necessary thermodynamic data from a previously developed thermochemistry module. The gas phase reaction module has been used to improve the description of the gas burners and the freeboard of the EAF. The implementation of the gas phase reaction module has been found to be in good agreement with commercially available software (HSC Sim) for calculations assuming a gas phase equilibrium.
Decreasing the environmental impact of the electric steel making process through implementation of furnace retrofitting solutions
Authors: Kaiser F. , Reichel T. , Echterhof T. , Mier D. , Unamuno I. , Pfeifer H. 
Published: May 2024

Abstract
Steel production in the electric arc furnace is an energy-intensive process and generates a high amount of climate-relevant CO2 emissions. During the last decades, various improvements of the furnace and its operation have been developed and implemented, so that the efficiency of modern steel plants has reached a high level. Due to the standardized process flows and high production volumes, even small improvements in resource efficiency can lead to significant savings and improve the environmental impact of the steel production. This paper presents several optimization activities and retrofitting solutions for the metallurgical sector and in particular for the electric steel route. On the example of a Spanish electric steel plant, a life cycle analysis is carried out to calculate the potential improvements in environmental impacts and compare them with the current state of the art. For this purpose, real process data were collected and transferred to a life cycle assessment model with the use of a material flow analysis. A comparison of the ecological impact categories provides information on which retrofitting solutions can improve the process in the electric arc furnace and ensure a lower environmental impact.
Engineered K-doped ZnO/borneol based hydrogel composite material for led-based photocatalytic degradation of methylene blue and evaluation of antimicrobial activity
Authors: Zhang Weiyi , Zhang Dandan , Lv Huanzhi , Zhou Zhenjie , Wang Lingnan , Xie Shibing , Zheng Zexiang 
Published: May 2024

Abstract
The significant improvement of decolorization and disinfection technologies has been a hotspot in wastewater reutilization. In this study, we realized a novel construction of K-doped nano-ZnO and borneol based hydrogel composite material (K-ZnO/B-hydrogel) by low-temperature in situ sol–gel growth. The techniques such as fourier transform infrared (FTIR), X-ray diffraction (XRD), x-ray photoelectron spectroscopy (XPS), scanning electron microscope (SEM) and X-ray energy dispersive spectroscopy (EDS) were applied to recognize the synthesized hydrogel. The results revealed that K-doped ZnO nanoparticles had been uniformly decorated onto the B-hydrogel. Ultraviolet-visible (UV–vis) absorption spectra showed that impurity doping of potassium element into ZnO could reduce the band gap, improving the visible light absorption efficiency. Under LED illumination, the photodegrading rate of K-ZnO/B-hydrogel was approximately 2.3 times greater than that of K-ZnO/B-hydrogel on methylene blue (MB) removal. Remarkably, aside from CO2 and H2O, no by-products were generated during the photodegradation process. In addition, the antimicrobial activities against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) of K-ZnO/B-hydrogel achieved up to 99.9%, which were at least 1.5 times higher than K-ZnO/B-hydrogel. This composite will push ahead with a closed-loop wastewater treatment system for dye and pathogenic microorganism disposal, which combines the excellent adsorption ability of hydrogel and the outstanding photocatalytic ability of ZnO nanoparticles with easy sample handling and separation, and help to eliminate secondary pollution.
Production of complex Fe-Si-Mn-Cr ferroalloy using high-ash coal: a sustainable metallurgical approach
Authors: Makhambetov Ye , Gabdullin S , Zhakan A , Saulebek Zh , Akhmetov A , Zulhan Z , Mukanov S 
Published: May 2024

Abstract
The article presents the results of comprehensive thermodynamic modeling and laboratory tests conducted for smelting a complex ferroalloy of silicon, manganese, and chromium (Fe-Si-Mn-Cr) from chromium, medium-grade manganese ores, and high-ash coals from Kazakhstan. Thermodynamic analysis was performed using HSC Chemistry software to model the Fe-Si-Mn-Cr smelting process over a temperature range of 900 °C–1800 °C. This analysis involved six actual charge compositions with solid reductant (Csolid) consumption ranging from 5 to 20 kg per 100 kg of Cr and Mn ore mixture. The mechanism of the combined carbothermic reduction of Cr, Mn, Si, and Fe was investigated using the Cr-Si-Al-Ca-Mn-Mg-O-C system. According to thermodynamic data, the optimal consumption of Csolid per 100 kg of ore mixture is 17 kg, and the optimal temperature range for smelting ferroalloys is between 1600 and 1700 °C. Laboratory tests were conducted in a high-temperature Tamman furnace at 1700 °C, resulting in experimental samples of the new complex ferroalloy with an average composition of 14.85% Fe, 14.05% Si, 7.55% Mn, 57.54% Cr, and 6.01% C, with P < 0.03% and S < 0.02%. The phase composition included (Cr, Fe, Mn)3Si and carbides Cr23C6 and (Fe, Mn)3C. The resulting alloy is suitable for alloying high-carbon and tool steels.
An assessment of the infrastructural and temporal barriers constraining a near-term implementation of a global stratospheric aerosol injection program
Authors: Smith Wake 
Published: May 2024

Abstract
Models of stratospheric aerosol injection deployment scenarios have often assumed that a global sunscreen could be applied to the Earth on relatively short notice, perhaps in response to a climate emergency. This emergency response framing confuses the timescales associated with the commencement of such a program. Once deployed, stratospheric aerosols could cool the Earth quite quickly, but the most commonly assumed deployment scenarios would require aircraft and other infrastructure that does not currently exist. Given the span required to develop and certify a novel aircraft program and to subsequently build a fleet numbering in the hundreds, scenario builders should assume a roughly two-decade interval between a funded launch decision and the attainment of a target level of cooling.
Catalyst integration within the air electrode in secondary Zn-air batteries
Authors: Labbe Matthew , Ivey Douglas G 
Published: May 2024

Abstract
The air electrode of a Zn-air battery facilitates the O2 reduction and evolution reactions during battery discharge and charge, respectively. These reactions are kinetically sluggish and appropriate catalysts are essential at the air electrode to increase battery efficiency. Precious metals are traditionally used, but increasingly attention has shifted towards non-precious metal catalysts to decrease the cost and increase the practicality of Zn-air batteries. However, loading of the catalyst onto the air electrode is equally as important as catalyst selection. Several methods can be used to deposit catalysts, each with their own advantages and disadvantages. Example methods include spray-coating, electrodeposition, and impregnation. These can be categorized as indirect, direct, and hybrid catalyst loading techniques, respectively. Direct and hybrid loading methods generally provide better depth of loading than indirect methods, which is an important consideration for the porous, air-breathing electrode of a Zn-air battery. Furthermore, direct methods are free from ancillary materials such as a binder, required by indirect and hybrid methods, which translates into better cycling stability. This review examines the various techniques for fabricating catalyst-enhanced air electrodes with an emphasis on their contributions to battery performance and durability. More durable Zn-air battery air electrodes directly translate to longer operational lifetimes for practical Zn-air batteries, which is an important consideration for the future implementation of electrochemical energy storage in energy systems and technologies. Generally, direct catalyst loading techniques, which integrate catalyst material directly onto the air electrode structure, provide superior cycling performance to indirect catalyst loading techniques, which distribute an ex-situ synthesized material onto the top layer of the air electrode. Hybrid catalyst loading techniques, which grow catalyst material directly onto nanostructured supports and then integrate them throughout the air electrode architecture, offer a compromise between direct and indirect methods.
Effect of zirconium carbide coating on thermal behavior of heavy duty V12 diesel engine using finite element method
Authors: Zaman Muhammad Farooq , Bukhari Syed Masood Arif , Husnain Naveed , Abbas Zulkarnain , Ayyub Aqib , Najmi Muhammad Furqan , Manan Abdul , Zahid Muhammad 
Published: May 2024

Abstract
Thermal losses and emissions are considered as major contributing factors in decreasing the efficiency of engines and life span of engines. To prevent heat losses and emissions, thermal ceramic coatings are considered as potential contenders. Moreover, ceramic coatings also prevent engine parts from damage due to thermal stresses. In this computational study, the effect of Zirconium Carbide coating on the thermal behavior of V12 engine is explored. Geometry of V12 engine’s piston and cylinder is generated in SolidWorks 2016. After that, piston’s surface and cylinder’s inner walls are coated with Zirconium Carbide ceramic coating and thermal behavior is analyzed using ANSYS Workbench 19.2. Two cases are discussed in this work. In the first case, piston is made of Al-3003 alloy and cylinder walls are made of gray cast iron whereas in the second case, whole assembly is made of Al-3003 alloy. Temperature and heat flux profiles of both the cases are compared with coating and without coating. Maximum temperature is recorded to be at the top of piston head surface. The results show 44.9% increase in maximum temperature for the first case whereas 83.5% increase in the second case. Heat flux results after show reduction after coating. Zirconium Carbide ceramic coatings can act as thermal barrier and prevent engine parts from thermal stresses. Moreover, it provides insulation to cylinder which prevents heat transfer and retains more temperature inside the cylinder which in turn enhances the efficiency.
Introducing a machine learning algorithm for delirium prediction—the Supporting SURgery with GEriatric Co-Management and AI project (SURGE-Ahead)
Authors: Benovic Samuel , Ajlani Anna H , Leinert Christoph , Fotteler Marina , Wolf Dennis , Steger Florian , Kestler Hans , Dallmeier Dhayana , Denkinger Michael , Eschweiler Gerhard W , Thomas Christine , Kocar Thomas D 
Published: May 2024

Abstract

Introduction
Post-operative delirium (POD) is a common complication in older patients, with an incidence of 14–56%. To implement preventative procedures, it is necessary to identify patients at risk for POD. In the present study, we aimed to develop a machine learning (ML) model for POD prediction in older patients, in close cooperation with the PAWEL (patient safety, cost-effectiveness and quality of life in elective surgery) project.

Methods
The model was trained on the PAWEL study’s dataset of 878 patients (no intervention, age ≥ 70, 209 with POD). Presence of POD was determined by the Confusion Assessment Method and a chart review. We selected 15 features based on domain knowledge, ethical considerations and a recursive feature elimination. A logistic regression and a linear support vector machine (SVM) were trained, and evaluated using receiver operator characteristics (ROC).

Results
The selected features were American Society of Anesthesiologists score, multimorbidity, cut-to-suture time, estimated glomerular filtration rate, polypharmacy, use of cardio-pulmonary bypass, the Montreal cognitive assessment subscores ‘memory’, ‘orientation’ and ‘verbal fluency’, pre-existing dementia, clinical frailty scale, age, recent falls, post-operative isolation and pre-operative benzodiazepines. The linear SVM performed best, with an ROC area under the curve of 0.82 [95% CI 0.78–0.85] in the training set, 0.81 [95% CI 0.71–0.88] in the test set and 0.76 [95% CI 0.71–0.79] in a cross-centre validation.

Conclusion
We present a clinically useful and explainable ML model for POD prediction. The model will be deployed in the Supporting SURgery with GEriatric Co-Management and AI project.