bluuebunny/crossref_metadata_2025 huggingface dataset:
High-efficiency and easy-processing thin-film lithium niobate edge coupler
Authors: Jia Di , Luo Qiang , Yang Chen , Ma Rui , Yu Xuanyi , Gao Feng , Yang Qifan , Bo Fang , Zhang Guoquan , Xu Jingjun
Published: October 2024

Fiber-to-chip coupling with ultralow loss and broadband operation wavelength range is essential in the practical applications of thin-film lithium niobate (TFLN) integrated photonic devices. However, the existing edge couplers often require electron beam lithography overlaying and multiple etching processes, which are expensive and complex. In this Letter, we demonstrate an edge coupler that includes only a vertically tapered TFLN waveguide and silicon dioxide cladding. The coupling efficiency between a lensed fiber and an on-chip LN waveguide is down to 1.43 dB/facet, while the 3-dB bandwidth exceeds the range from 1510 to 1630 nm. These edge couplers also show reliable fiber misalignment tolerance. Furthermore, the fabrication complexity is greatly reduced since only a single etching step for the TFLN waveguide is needed. The minimum waveguide width of 1.3 μm guarantees compatibility with i-line photolithography, providing a potential for massive production of TFLN devices.
Achieving high piezoelectric performance in Pb(Mg1/3Nb2/3)O3–PbTiO3 ferroelectric single crystals through pulse poling technique
Authors: Chen Shuli , Gai Xuezhou , Xiong Ruibin , Liang Min , Wang Zujian , Su Bin , Su Rongbing , Liu Jianqun , Liu Ying , He Chao
Published: October 2024

To maximize the piezoelectric performance of Pb(Mg1/3Nb2/3)O3–PbTiO3 (PMN–PT) single crystals, a pulse poling (PP) method is proposed in this study. This study investigates the effects of pulse poling on the piezoelectric and dielectric properties of these PMN–PT single crystals and explores the polarization rotation mechanisms. Our findings indicate a significant improvement in the piezoelectric properties postpulse poling. The optimal PP conditions are identified as 30 pulse numbers at a pulsed electric field of 5 kV/cm. The dielectric constant ɛT33/ɛ0 and piezoelectric coefficient d33 of PMN–0.28PT post PP are 7000–7700 and 2200–2530 pC/N, respectively, representing increases of 49% and 66% compared with those of postdirect current poling (DCP). Additionally, the domain structures of the PMN–0.28PT single crystals after various DCP and PP treatments are examined and compared using piezoelectric force microscopy. The enhanced piezoelectric properties are attributed to the finer domain structures, as well as increased domain wall density achieved through PP. This research introduces a novel domain engineering approach to improve the electromechanical properties of relaxor ferroelectric single crystals.
TE-polarized leaky-wave beam launchers: Generation of Bessel and Bessel–Gauss beams
Authors: Negri E. , Fuscaldo W. , González-Ovejero D. , Burghignoli P. , Galli A.
Published: October 2024

The generation of focused beams in the millimeter- and submillimeter-wave ranges, with transverse-electric (TE) polarization, is investigated in the radiative near-field region. The desired field distribution is achieved through a leaky-wave beam launcher consisting of a grounded dielectric slab with an annular strip grating on top excited by a circular slot on the bottom ground plane. The latter is fed by a Marié transducer, which converts the input, fundamental TE10 mode of a standard rectangular waveguide into the higher-order TE01 mode propagating in the circular waveguide connected to the device. The generation of TE-polarized diffraction-limited Bessel and Bessel–Gauss distributions is achieved by suitably synthesizing the annular strip grating. Simulated results are in excellent agreement with those predicted by leaky-wave analysis providing a proof-of-concept for the generation of TE-polarized Bessel and Bessel–Gauss beams at 300 GHz with a beam size of 1.7 and 1.9 mm up to the nondiffractive range of about 25 and 15 mm from an aperture plane with radius of 12.75 mm, respectively.
Shock wave interaction with a naturally generated vortex ring
Authors: Ahire Swapnil Ashok , Chatterjee Avijit
Published: October 2024

The vortex ring is usually analytically modeled in computational studies involving vortex ring and shock wave interaction. However, incompressibility assumptions of the isolated vortex ring model mostly limits its applicability to the lower Mach number regime. To overcome this limitation, a compressible vortex ring is generated using a pulse jet exiting a circular nozzle, and its interaction with a shock wave is analyzed. The shock–vortex interaction and resulting sound wave generation is simulated by solving the compressible axisymmetric Navier–Stokes equations. A characteristics-based filter is used to isolate acoustic and hydrodynamic disturbances in the flow field. A reconfigured computational domain is used to negate the aftereffects of the nozzle on the flow field. The strong interaction of compressible vortex rings at higher Mach numbers with different shock wave Mach numbers in the flow field is studied including resultant acoustic wave generation.
ETHOS: An automated framework to generate multi-fidelity constitutive data tables and propagate uncertainties to hydrodynamic simulations
Authors: Stanek Lucas J. , Lewis William E. , Cochrane Kyle R. , Jennings Christopher A. , Desjarlais Michael P. , Hansen Stephanie B.
Published: October 2024

Accurate constitutive data, such as equations of state and plasma transport coefficients, are necessary for reliable hydrodynamic simulations of plasma systems such as fusion targets, planets, and stars. Here, we develop a framework for automatically generating transport-coefficient tables using a parameterized model that incorporates data from both high-fidelity sources (e.g., density functional theory calculations and reference experiments) and lower-fidelity sources (e.g., average-atom and analytic models). The framework incorporates uncertainties from these multi-fidelity sources, generating ensembles of optimally diverse tables that are suitable for uncertainty quantification of hydrodynamic simulations. We illustrate the utility of the framework with magnetohydrodynamic simulations of magnetically launched flyer plates, which are used to measure material properties in pulsed-power experiments. We explore how changes in the uncertainties assigned to the multi-fidelity data sources propagate to changes in simulation outputs and find that our simulations are most sensitive to uncertainties near the melting transition. The presented framework enables computationally efficient uncertainty quantification that readily incorporates new high-fidelity measurements or calculations and identifies plasma regimes where additional data will have high impact.
A targeted study to determine the conservation status of a Data Deficient montane lizard, the Eungella shadeskink (Saproscincus eungellensis)
Authors: Scott Nicholas A. , Mulder Jordan , Pili Arman N. , Oliver Paul M. , Hines Harry B. , Farquhar Jules E. , Chapple David G.
Published: October 2024

Context Combatting biodiversity loss is often hamstrung by a lack of species-specific knowledge. Species considered Data Deficient (DD) on the IUCN Red List are poorly understood and often neglected in conservation investment, despite evidence they are often threatened. Reptiles have the highest percentage of DD species for any terrestrial vertebrate group. Aims We aimed to assess the conservation status of the DD Eungella shadeskink (Saproscincus eungellensis), which is endemic to Eungella National Park, Queensland, Australia. Methods A combination of a targeted field survey, ecological studies, and species distribution modelling were used. Key results Saproscincus eungellensis typically occurred within 25 m of streams, at elevations between 700 and 1000 m. The species is thigmothermic, with a low active body temperature (~23–26°C) and was predominantly observed on rocks and fallen palm fronds. The species has a highly restricted distribution with an estimated Area of Occupancy of 36 km2 and Extent of Occurrence of 81.7 km2, comprising one location (defined by the threat of climate change) with an estimated 16,352–52,892 mature individuals. The main threats are fire, invasive alien species and climate change, with the species forecast to lose all suitable habitat by 2080 under all climate change scenarios. Conclusions The species meets listing criteria for Critically Endangered under Criterion B of the International Union for Conservation of Nature. Implications Our results support recent studies indicating that some DD species are highly threatened. Our approach provides a template for conducting targeted studies to determine the conservation status of DD species, especially those with restricted ranges.
Standing on the shoulders of giants: molecular data confirm Kükenthal’s systematic placement of the Australian endemic Carex archeri (Cyperaceae)
Authors: Morales-Alonso Ana , Wilson Karen , Ford Kerry A. , Míguez Mónica , Jiménez-Mejías Pedro , Martín-Bravo Santiago
Published: October 2024

Archer’s sedge (Carex archeri Boott) is a small, rare (or possibly overlooked by collectors due to the diminutive size) species restricted to alpine and subalpine habitats in south-eastern mainland Australia and Tasmania. The systematic placement has been obscure with the species having been historically associated with sections in four of the six recognised Carex subgenera. We investigated the placement of C. archeri by addition to the available Carex molecular phylogenetic framework. Our results support C. archeri belonging to sect. Junciformes (in subg. Psyllophorae), making this the only representative of the subgenus in Australia. This placement was first proposed by Kükenthal (1909) who regarded C. archeri as a synonym of the New Zealand endemic C. acicularis Boott but our phylogenetic analyses support C. archeri as a separate taxon. Our approach highlights the utility of molecular barcoding for elucidating systematic relationships of poorly known taxa. Biogeographic reconstruction suggests Late Miocene dispersal from South America to the south-western Pacific but does not clarify whether New Zealand or Australia was colonised first. We evaluate the conservation status of Carex archeri using IUCN criteria as Endangered at the global level. At the state level, we propose Critically Endangered status in New South Wales, Endangered in Victoria and Data Deficient in Tasmania.
Girrimarring wiirrilgal bulany ngayanbading (bat nest-type fur sun-like): blending traditional knowledge and western science to create roosting habitat for the threatened golden-tipped bat Phoniscus papuensis
Authors: Lloyd Anna , Scanlon Alicia , Clegg Lilly , Link Ruth , Jarrett Lauren , Pursch Kristy , Williams Alison , Giese Melissa
Published: October 2024

Context Despite being widely distributed along eastern Australia, the golden-tipped bat (Phoniscus papuensis) is listed as Vulnerable in New South Wales (NSW). The 2019–2020 wildfires affected an estimated 40% of foraging and roosting habitat, causing further conservation concern. The species roosts in suspended birds’ nests located along watercourses in rainforest or wet sclerophyll forests. Habitat augmentation is a key recovery action for the species; however, effective techniques are unknown. Aims We integrated western scientific and Indigenous cultural knowledge and practice to deliver an artificial roosting structure for golden-tipped bats, and designed and implemented a collaborative model for habitat restoration, with genuine opportunity for cultural practice and two-way knowledge sharing. Methods In partnership, members of Indigenous groups, western scientific organisations and volunteers shared learnings about bats, culture and caring for Country. Weaving materials were collected from local forests, roosts were woven and hung in rainforest gullies and monitored using remote cameras and direct visual inspection. Key results Golden-tipped bats used woven roosts, suggesting that roosting-habitat augmentation could support recovery of the species. Strong partnerships were established between government conservation programs and local Indigenous communities, engaging younger generations in cultural practice and learning. Delivery models were demonstrated for further collaborative, two-way threatened species projects. Conclusions Golden-tipped bats will use woven structures for roosting. Integrating Indigenous knowledge into threatened species programs can deliver effective conservation outcomes for specialist and cryptic species. Implications Should further broadscale fire, or other impact causing loss of roosting structures occur, community, Indigenous groups or government agencies can utilise this model to implement effective conservation actions together.
Deficiency of
DDX3X
results in neurogenesis defects and abnormal behaviors via dysfunction of the Notch signaling
Authors: Duan Weicheng , Huang Guiyang , Sui Yang , Wang Kang , Yu Yuxin , Chu Xufeng , Cao Xu , Chen Liangpei , Liu Jiahui , Eichler Evan E. , Xiong Bo
Published: October 2024

The molecular mechanisms underlying the neurodevelopmental disorders (NDDs) caused by
DDX3X
variants remain poorly understood. In this study, we validated that de novo
DDX3X
variants are enriched in female developmental delay (DD) patients and mainly affect the evolutionarily conserved amino acids based on a meta-analysis of 46,612 NDD trios. We generated a
ddx3x
deficient zebrafish allele, which exhibited reduced survival rate, DD, microcephaly, adaptation defects, anxiolytic behaviors, social interaction deficits, and impaired spatial recognitive memory. As revealed by single-nucleus RNA sequencing and biological validations,
ddx3x
deficiency leads to reduced neural stem cell pool, decreased total neuron number, and imbalanced differentiation of excitatory and inhibitory neurons, which are responsible for the behavioral defects. Indeed, the supplementation of L-glutamate or glutamate receptor agonist ly404039 could partly rescue the adaptation and social deficits. Mechanistically, we reveal that the
ddx3x
deficiency attenuates the stability of the
crebbp
mRNA, which in turn causes downregulation of Notch signaling and defects in neurogenesis. Our study sheds light on the molecular pathology underlying the abnormal neurodevelopment and behavior of NDD patients with
DDX3X
mutations, as well as providing potential therapeutic targets for the precision treatment.
Experimental coral reef communities transform yet persist under mitigated future ocean warming and acidification
Authors: Jury Christopher P. , Bahr Keisha D. , Cros Annick , Dobson Kerri L. , Freel Evan B. , Graham Andrew T. , McLachlan Rowan H. , Nelson Craig E. , Price James T. , Rocha de Souza Mariana , Shizuru Leah , Smith Celia M. , Sparagon Wesley J. , Squair Cheryl A. , Timmers Molly A. , Vicente Jan , Webb Maryann K. , Yamase Nicole H. , Grottoli Andréa G. , Toonen Robert J.
Published: October 2024

Coral reefs are among the most sensitive ecosystems affected by ocean warming and acidification, and are predicted to collapse over the next few decades. Reefs are predicted to shift from net accreting calcifier-dominated systems with exceptionally high biodiversity to net eroding algal-dominated systems with dramatically reduced biodiversity. Here, we present a two-year experimental study examining the responses of entire mesocosm coral reef communities to warming (+2 °C), acidification (−0.2 pH units), and combined future ocean (+2 °C, −0.2 pH) treatments. Contrary to modeled projections, we show that under future ocean conditions, these communities shift structure and composition yet persist as novel calcifying ecosystems with high biodiversity. Our results suggest that if climate change is limited to Paris Climate Agreement targets, coral reefs could persist in an altered state rather than collapse.
How working from home reshapes cities
Authors: Ramani Arjun , Alcedo Joel , Bloom Nicholas
Published: October 2024

In recent decades, economic activity has become increasingly concentrated in major global metropolises. Yet, the rise of working from home threatens this dominance of cities. Using multiple high-frequency datasets on spending, commuting, migration, and housing, we provide global evidence that remote work has dispersed economic activity away from city centers. We label this the “Donut Effect,” which is much larger and more persistent in cities with high levels of remote work. Using detailed household microdata from the United States, we show that three-fifths of households that left city centers in big cities moved to the suburbs of the same city. This is likely explained by the rise of hybrid work, in which employees still commute to the office a few days a week. The enduring popularity of hybrid work into 2024 suggests that the Donut Effect will persist while also leaving broader metropolitan areas intact.
A molecular view of peptoid-induced acceleration of calcite growth
Authors: Zhang Mingyi , Chen Ying , Wu Chunhui , Zheng Renyu , Xia Ying , Saccuzzo Emily G. , Trinh Thi Kim Hoang , Mondarte Evan Angelo Quimada , Nakouzi Elias , Rad Behzad , Legg Benjamin A. , Shaw Wendy J. , Tao Jinhui , De Yoreo James J. , Chen Chun-Long
Published: October 2024

The extensive deposits of calcium carbonate (CaCO
3
) generated by marine organisms constitute the largest and oldest carbon dioxide (CO
2
) reservoir. These organisms utilize macromolecules like peptides and proteins to facilitate the nucleation and growth of carbonate minerals, serving as an effective method for CO
2
sequestration. However, the precise mechanisms behind this process remain elusive. In this study, we report the use of sequence-defined peptoids, a class of peptidomimetics, to achieve the accelerated calcite step growth kinetics with the molecular level mechanistic understanding. By designing peptoids with hydrophilic and hydrophobic blocks, we systematically investigated the acceleration in step growth rate of calcite crystals using in situ atomic force microscopy (AFM), varying peptoid sequences and concentrations, CaCO
3
supersaturations, and the ratio of Ca
2+
/ HCO
3
−
. Mechanistic studies using NMR, three-dimensional fast force mapping (3D FFM), and isothermal titration calorimetry (ITC) were conducted to reveal the interactions of peptoids with Ca
2+
and HCO
3
−
ions in solution, as well as the effect of peptoids on solvation and energetics of calcite crystal surface. Our results indicate the multiple roles of peptoid in facilitating HCO
3
−
deprotonation, Ca
2+
desolvation, and the disruption of interfacial hydration layers of the calcite surface, which collectively contribute to a peptoid-induced acceleration of calcite growth. These findings provide guidelines for future design of sequence-specific biomimetic polymers as crystallization promoters, offering potential applications in environmental remediation (such as CO
2
sequestration), biomedical engineering, and energy storage where fast crystallization is preferred.
Phraseological sophistication as a multidimensional construct
Authors: Paquot Magali , Naets Hubert
Published: October 2024

Since Paquot (2019), several unresolved issues have persisted regarding
the operationalization of phraseological sophistication in L2 complexity research. One of the most crucial concerns relates to the
extent to which the commonly used measures of phraseological sophistication (MI scores) fully represent the intended construct. In
this study, we draw upon insights from L2 phraseological research to reexamine the conceptualization and operationalization of
phraseological sophistication. We conduct new analyses on the learner corpus used in Paquot
(2019), using alternative operationalizations of phraseological sophistication that represent different dimensions of
sophistication (based on the register specificity of word combinations and their frequency). Results show that measures
representing the dimensions of association (MI scores) and register specificity (ratios of academic collocations) correlate with
each other. Frequency-based measures, however, pattern very differently, which we attribute to some issues in the way we
operationalized frequency of co-occurrence.
Temperature-dependent properties of wurtzite and rock salt Al1−xScxN for applications in BAW resonators
Authors: Mihalic S , Wade E , Ott P , Ambacher O
Published: October 2024

Aluminum scandium nitride (Al

1
−
x

Sc
x
N) is known for its tremendous enhancement of piezoelectric properties. This material can improve the energy efficiency of a wide range of applications, for example bulk acoustic wave (BAW) resonators. Such devices heat up during operation and are thus sensitive to temperature-dependent material properties. As a result, device characteristics change with temperature, causing undesirable shifts in achievable frequency and performance. These shifts are well known for AlN-based resonators, where the frequency shifts are compensated without increasing the bandwidth of the frequency filter. For the ternary alloy Al

1
−
x

Sc
x
N, many temperature-dependent structural, mechanical and piezoelectric properties have not or have been insufficiently investigated. This review provides an overview of relevant temperature dependent properties of hexagonal wurtzite (x

<

0.5) and cubic rock salt Al

1
−
x

Sc
x
N (x

>

0.5) crystals up to 2000 K. The properties studied are the thermal expansion coefficient α, the elastic tensor C

i
j

, the piezoelectric coefficient d
33, the piezoelectric stress coefficient e
33 and the permittivity ɛ
33. Based on these material properties, the derived characteristics for BAW resonators are determined from 0 to 1400 K, which are the resonance frequency f

R
and the electromechanical coupling coefficient k

t

2

.
A novel cascading partial ambiguity resolution method of BDS triple-frequency with inertial aiding for kinematic-to-kinematic relative positioning
Authors: Fu Xiyu , Zhao Kedong , Sun Yongrong , Xu Shuchen , Li Yao
Published: October 2024

The integer ambiguity resolution (AR) of the carrier phase is crucial for high-precision positioning. To solve the problem that the three carrier ambiguity resolution method will not be reliable when the observation quality cannot meet the requirement under the kinematic-to-kinematic condition, a novel cascading partial AR method of BeiDou navigation satellite system triple-frequency with inertial aiding for kinematic-to-kinematic relative positioning is proposed. At first, inertial data is utilized to improve the reliability and robustness of the extra wide lane AR in dynamic environments. Meanwhile, to improve the fixed success rate, the wide lane ambiguity is obtained by a linear combination of dual extra wide lane with inertial aiding indirectly. For the most challenging narrow-lane ambiguity, a Geometry-based enhanced mode is individually developed for the model constraint, in which a partial AR method for narrow lane with float solution filtered is designed to improve the fixed success rate under the GB model. Finally, the simulation and practical experiment were conducted to verify the effectiveness of the proposed method. The results show that the proposed method can effectively improve the fixed success rate of ambiguity under the kinematic-to-kinematic conditions, which can reach about 99.54% and achieve cm-level relative positioning in dynamic environments.
A Monte Carlo study on a 3-dimensional comb polymer translocation through a nanopore driven by an electric field
Authors: Bruh Tesfa B , Tatek Yergou B
Published: October 2024

A lattice Monte Carlo simulation study of the translocation of comb polymers through a nanopore subjected to an electric field is presented. The translocation dynamics was extensively studied in terms of the applied electric field strength, the pore size, and the comb polymer topology. The variations of the most probable translocation time

τ

p

and the mean translocation time

⟨
τ
⟩

as a function of the applied electric field strength show distinct features, the latter exhibiting a nonmonotonic dependence on the electric field. We were able to show the existence of a critical field strength δε

c
defined by the narrowest distribution of the translocation time, which is closely related to the size of the nanopore. In addition, we have found that the critical field strength also defines a transition point between two regimes of translocation: a smooth translocation for a field strength below δε

c
and a chaotic translocation for a field strength above δε

c
. Moreover, for the smallest pore size (

r

p

=
1

), monomers can only cross the nanopore in a single file, while for larger pores different modes of polymer translocation are identified. Finally, the dependence of the mean translocation time on the backbone length is governed by a power law relationship

⟨
τ
⟩

∼

N

B

α

, where the scaling exponent α is found to be in the range of 1.3–1.7 for the set of side chain lengths and nanopore sizes investigated. As for the side chain length

N

S

, the mean translocation time is found to follow a linear dependence

⟨
τ
⟩

∼

N

S

.
Enhancing mycotoxins detection through quantum dots-based optical biosensors
Authors: Dadmehr Mehdi , Shalileh Farzaneh , Hosseini Morteza
Published: October 2024

Quantum dot-based optical biosensors represent a significant advancement for detection of mycotoxins that are toxic secondary metabolites produced by fungi and pose serious health risk effects. This review highlights the importance of detection of filamentous fungi such as Aspergillus, Penicillium, Fusarium, Claviceps, and Alternaria in mycotoxin production, leading to contamination of agricultural products and subsequent health issues. Conventional detection methods such as thin-layer chromatography, high-performance liquid chromatography, gas chromatography, and enzyme-linked immunosorbent assay are discussed with their respective advantages and limitations. Then the innovative use of quantum dots (QDs) in fabrication of biosensors is discussed in the present review, emphasizing their unique optical properties, such as size-tunable fluorescence and high photostability. These properties enable the development of highly sensitive and specific biosensors for mycotoxin detection. The application of QD-based biosensors, based on their applied bioreceptors including antibodies, molecularly imprinted polymers and aptamer, is explored through various detection strategies and recent advancements. The review concludes by underscoring the potential of QD-based biosensors in providing portable, cost-effective, and efficient solutions for real-time monitoring of mycotoxin for enhancing food safety and protecting public health.
Deep learning prediction of scenario doses for direct plan robustness evaluations in IMPT for head-and-neck
Authors: Nomer Hazem A A , Knuth Franziska , van Genderingen Joep , Nguyen Dan , Sattler Margriet , Zolnay András , Oelfke Uwe , Jiang Steve , Rossi Linda , Heijmen Ben J M , Breedveld Sebastiaan
Published: October 2024

Objective. Intensity modulated proton therapy (IMPT) is susceptible to uncertainties in patient setup and proton range. Robust optimization is employed in IMPT treatment planning to ensure sufficient coverage of the clinical target volume (CTV) in predefined scenarios, albeit at a price of increased planning times. We investigated a deep learning (DL) strategy for dose predictions in individual error scenarios in head and neck cancer IMPT treatment planning, enabling direct evaluation of plan robustness. The model is able to differentiate between scenarios by using embeddings of the scenario index. Approach. To accommodate resolution disparities in planning CT-scans and accommodate the setup error scenarios, we introduced scenario-specific isocentric distance maps as inputs to the DL models. For 392 H&N cancer patients, high-quality 9-scenario ground truth (GT) robust plans were generated with wish-list driven fully automated multi-criteria optimization. The scenario index is converted to one-hot-vector that is used to derive the scenarios embeddings through the training of the DL model, aiding the model to predict a scenario specific dose distribution. Main results. The model achieved within 1%-point of agreement with the GT the predicted

V

95
%

of the voxelwise minimum dose for CTV Low and CTV High for 96% and 75% respectively of the test patients. Considering all robustness scenarios, median differences were 0.035%-point for CTV High

V

95
%

, 0.11%-point for CTV Low

V

95
%

, 0.29 GyE for parotids

D

mean

, 0.7 GyE for submandibular glands

D

mean

and 0.9 GyE for oral cavity

D

mean

. Prediction of full 3D dose distributions for all scenarios took around 14 s. Significance. Predicting individual scenarios for robust proton therapy using DL dose prediction is feasible, enabling direct robustness evaluation of the predicted scenario doses.
Hybrid plug-and-play CT image restoration using nonconvex low-rank group sparsity and deep denoiser priors
Authors: Liu Chunyan , Li Sui , Hu Dianlin , Zhong Yuxiang , Wang Jianjun , Zhang Peng
Published: October 2024

Objective. Low-dose computed tomography (LDCT) is an imaging technique that can effectively help patients reduce radiation dose, which has attracted increasing interest from researchers in the field of medical imaging. Nevertheless, LDCT imaging is often affected by a large amount of noise, making it difficult to clearly display subtle abnormalities or lesions. Therefore, this paper proposes a multiple complementary priors CT image reconstruction method by simultaneously considering both the internal prior and external image information of CT images, thereby enhancing the reconstruction quality of CT images. Approach. Specifically, we propose a CT image reconstruction method based on weighted nonconvex low-rank regularized group sparse and deep image priors under hybrid plug-and-play framework by utilizing the weighted nonconvex low rankness and group sparsity of dictionary domain coefficients of each group of similar patches, and a convolutional neural network denoiser. To make the proposed reconstruction problem easier to tackle, we utilize the alternate direction method of multipliers for optimization. Main results. To verify the performance of the proposed method, we conduct detailed simulation experiments on the images of the abdominal, pelvic, and thoracic at projection views of 45, 65, and 85, and at noise levels of

1
×

10

5

and

1
×

10

6

, respectively. A large number of qualitative and quantitative experimental results indicate that the proposed method has achieved better results in texture preservation and noise suppression compared to several existing iterative reconstruction methods. Significance. The proposed method fully considers the internal nonlocal low rankness and sparsity, as well as the external local information of CT images, providing a more effective solution for CT image reconstruction. Consequently, this method enables doctors to diagnose and treat diseases more accurately by reconstructing high-quality CT images.
Microwave-optical spectroscopy of Rydberg excitons in the ultrastrong driving regime
Authors: Brewin Alistair , Gallagher Liam A P , Pritchett Jonathan D , Wong Horatio Q X , Potvliege Robert M , Clark Stewart J , Jones Matthew P A
Published: October 2024

We study the ultrastrong driving of Rydberg excitons in Cu2O by a microwave field. The effect of the field is studied using optical absorption spectroscopy, and through the observation of sidebands on the transmitted laser light. A model based on Floquet theory is constructed to study the system beyond the rotating wave approximation. We obtain near quantitative agreement between theory and experiment across a 16-fold range of microwave field strengths spanning from the perturbative to the deep strong driving regime. Compared to Rydberg atoms, the large non-radiative widths of Rydberg excitons leads to new behaviour such as the emergence of an absorption continuum without ionization.
Correlation analysis of composition, microstructure, and final properties of porcelain tiles: an experimental study
Authors: Zamani Mohsen , Yapicioglu Haluk , Kara Alpagut , Sevik Cem
Published: October 2024

This study deals with the intricate relationship between composition, microstructure and the final properties of porcelain tiles namely bulk density, water absorption, thermal expansion coefficient, strength, and Young’s modulus. In order to achieve this, a comprehensive set of 16 experimental trials were carried out, involving the preparation of eight distinct formulations characterized by varying Seger values and ratios which were subsequently subjected to sintering at two distinct firing temperatures. The analysis was conducted through a comprehensive correlation matrix, revealing significant relationships between composition, phase content and the final properties. The glassy phase emerges as a key contributor, positively influencing bulk density, reducing water absorption and linear shrinkage, and enhancing Young’s modulus. The coefficient of thermal expansion correlates positively with residual quartz and inversely with mullite content, highlighting their impact on this property. Strength is positively correlated with mullite content, while quartz, albite, and anorthite phases exhibit negative correlations due to their intricate influence on the overall microstructure. These findings provide essential insights into the complex interplay between composition, microstructure and properties, contributing to the advancement of materials engineering for tailored porcelain tiles.
Physics-informed neural networks approach for pollutant dispersion flow caused by magnetic dipole
Authors: Punith Gowda R. J. , Beemkumar N. , Kulshreshta Ankur , Chohan Jasgurpreet Singh , Abdulrahman Amal , Chandan K
Published: October 2024

Research on the liquid flow and distribution of waste discharge concentration over cylindrical surfaces might lead to the growth of efficient waste management and pollution controlling strategies. In view of this, the pollutant concentration and magnetic dipole impact on the liquid flow through the cylinder with a porous medium are explored in the present analysis. Moreover, Fourier’s and Fick’s laws are considered to explore heat transport features. The governing partial differential equations (PDEs) of the present study are converted into non-dimensional ordinary differential equations (ODEs) utilizing similarity variables. Also, the current study proposes a novel implementation of neural networks based on physics knowledge for the liquid flow past a cylinder. The self-updating weights and bias facilitate the network to satisfy the minimization objective function and provide accurate results. Additionally, the solution obtained by Runge Kutta Fehlberg's fourth-fifth order (RKF-45) method is utilized to validate the physics-informed neural network (PINN) results, presenting mean squared errors from 10-9 to 10-11. Furthermore, it is found that the increase in temperature relaxation time parameter decreases the Nusselt number gradually at the rate of 1 to 5%. An upsurge in the values of the pollutant external source parameter and the pollutant external source variation parameter decreases the concentration profile.
Analyzing Stellar Spectra for PRV by Accurate Modeling and Retrieval of Telluric Absorption Features
Authors: Sung Keeyoon , Toon Geoffrey C. , Cale Bryson L. , Chen Pin , Vasisht Gautam , Rocha Graca M. , Gibson Rose K. , Oppenheimer Rebecca , Plavchan Peter , Beichman Charles A.
Published: October 2024

Ground-based Precision Radial Velocity (PRV) measurements are inevitably impeded by contamination from telluric absorption features, particularly in the infrared region. Thus, it is crucial to improve modeling of the telluric absorption features down to the spectral noise level. As part of the efforts towards improved PRV measurements, we have taken an existing atmospheric trace gas retrieval algorithm (GFIT) and have successfully adapted it to fit the telluric absorption features in stellar spectra down to the spectral noise level (typically ∼1%). We have established a stellar spectral fitting processing pipeline, Stellar-GFIT, to analyze a series of stellar spectra observed by two spectrographs, PARVI (1.1–1.76 μm) commissioned at the Palomar Observatory (Palomar Mountain, CA) and iSHELL (1–5 μm) deployed on the IRTF (Mauna Kea, HI). For this, we have (1) implemented a Gaussian instrumental line shape function, (2) generated atmospheric models (consisting of temperature, pressure, and volume mixing ratios of all the known trace gases) for the particular observation sites and times, (3) employed the most up-to-date spectroscopic parameters in the target spectral regions, and finally (4) developed a series of spectral fitting intervals of ∼60 cm−1 width, i.e., micro-windows, customized to the individual orders of each spectrograph. Stellar-GFIT is also capable of handling non-telluric features, such as transitions from a gas cell placed in the starlight beam and stellar features if a model spectrum template is available for the target star. We present spectrum fits from the observations of various target stars and discuss the performance and advantages of our novel approach. One of the major strengths of Stellar-GFIT is an ability to adjust the abundance of atmospheric trace gases simultaneously with determining the stellar doppler shift, mitigating any adverse impacts of short-timescale variations of water vapor.
Activation thresholds for electrical phrenic nerve stimulation at the neck: evaluation of stimulation pulse parameters in a simulation study
Authors: Wegert Laureen , Ziolkowski Marek , Kalla Tim , Lange Irene , Haueisen Jens , Hunold Alexander
Published: October 2024

Objective. Phrenic nerve stimulation reduces ventilator-induced-diaphragmatic-dysfunction, which is a potential complication of mechanical ventilation. Electromagnetic simulations provide valuable information about the effects of the stimulation and are used to determine appropriate stimulation parameters and evaluate possible co-activation. Approach. Using a multiscale approach, we built a novel detailed anatomical model of the neck and the phrenic nerve. The model consisted of a macroscale volume conduction model of the neck with 13 tissues, a mesoscale volume conduction model of the phrenic nerve with three tissues, and a microscale biophysiological model of axons with diameters ranging from 5 to 14 µm based on the McIntyre–Richardson–Grill-model for myelinated axons. This multiscale model was used to quantify activation thresholds of phrenic nerve fibers using different stimulation pulse parameters (pulse width, interphase delay, asymmetry of biphasic pulses, pulse polarity, and rise time) during non-invasive electrical stimulation. Electric field strength was used to evaluate co-activation of the other nerves in the neck. Main results. For monophasic pulses with a pulse width of 150 µs, the activation threshold depended on the fiber diameter and ranged from 20 to 156 mA, with highest activation threshold for the smallest fiber diameter. The relationship was approximated using a power fit function x
−3. Biphasic (symmetric) pulses increased the activation threshold by 25 to 30 %. The use of asymmetric biphasic pulses or an interphase delay lowered the threshold close to the monophasic threshold. Possible co-activated nerves were the more superficial nerves and included the transverse cervical nerve, the supraclavicular nerve, the great auricular nerve, the cervical plexus, the brachial plexus, and the long thoracic nerve. Significance. Our multiscale model and electromagnetic simulations provided insight into phrenic nerve activation and possible co-activation by non-invasive electrical stimulation and provided guidance on the use of stimulation pulse types with minimal activation threshold.
Gyrokinetic prediction of core tungsten peaking in a WEST plasma with nitrogen impurities
Authors: Dominski J. , Maget P. , Manas P. , Morales J. , Ku S. , Scheinberg A. , Chang C.S. , Hager R. , O’Mullane M. ,   the WEST team
Published: October 2024

Tungsten peaking is predicted in the core of a WEST plasma with total-f gyrokinetic simulations, including both collisional and turbulent transport. This prediction is validated with a synthetic diagnostic of the bolometry. Although nitrogen impurities are shown to reduce the neoclassical peaking of tungsten on-axis, the overall tungsten peaking increases when nitrogen impurities are present, as they reduce the turbulence screening off-axis. This finding is important for the plasma current ramp-up phase of ITER, where light impurities seeding will be desirable to achieve low temperatures at the plasma-facing components and reduce tungsten sputtering. It provides further argument for applying early ECRH heating to maintain margins on the core power balance. The neoclassical peaking factor is cross-verified between XGC and FACIT. The heat flux at separatrix and the heat load width are modeled by XGC and compared to WEST data.
Future drought overestimations due to no constraints of CO2 physiological effect and land-atmosphere coupling on potential evapotranspiration
Authors: An Xuehua , Zhang Yifang , Sun Shanlei , Chai Rongfan , Bi Zaoying , Li Jinjian , Zhou Yang , Zhou Botao , Chen Haishan
Published: October 2024

Various offline drought indices have been widely used to project dryness/wetness and drought changes. However, the results derived from these indices often differ from or even contradict observations and direct projections made by coupled climate models. Therefore, it is crucial to investigate this scientific debate thoroughly and identify the potential causes. This study adopts a water demand-side perspective, focusing on potential evapotranspiration (PET), to address such controversy. Employing the Standardized Precipitation-Evapotranspiration Index (SPEI), three PET models including the Food and Agriculture Organization of the United Nations’ report 56 (FAO-56) Penman–Monteith (PM) model, a corrected FAO-56 PM model incorporating CO2 physiological effect (PMCO2), and a land-atmosphere coupled PET model (PET-LAC) are further compared. Despite projected increases in PET across most land areas, the PM shows the most pronounced increases among these PET models. Compared to PMCO2 and PET-LAC, the PM model predicts the most significant drying, with the 3-month SPEI decreasing by 0.50 ± 0.23 yr−1. Additionally, it projects the most substantial drought intensification, with increases in areas, intensity, and duration of 28 ± 6.9%, 0.70 ± 0.20 yr−1, and 2.90 ± 0.83 month yr−1, respectively. Meanwhile, these projections correspond to the most extensive area percentages, with 78.5 ± 10% for drying, 94.8 ± 7.2% for drought intensity, and 93.6 ± 7.9% for drought duration. These findings imply that the commonly used PM model overestimates future drought conditions. Differences and contradictions between the drought projections from PM-based offline indices and direct climate model outputs can be partly attributed to the omission of CO2 physiological effect and land-atmosphere coupling constraints in the PM model. This study highlights the importance of improving PET models by incorporating these constraints, thereby providing valuable insights for enhancing the accuracy of future drought assessments.
On the suitability of rigorous coupled-wave analysis for fast optical force simulations
Authors: Gao Bo , Gersen Henkjan , Hanna Simon
Published: October 2024

Optical force responses underpin nanophotonic actuator design, which requires a large number of force simulations to optimize structures. Commonly used computation methods, such as the finite-difference time-domain method, and finite element methods, are resource intensive and require large amounts of calculation time when multiple structures need to be compared during optimization. This research demonstrates that performing optical force calculations on 2D-periodic structures using the rigorous coupled-wave analysis method is typically on the order of 10 times faster than other approaches and with sufficient accuracy to suit optical design purposes. Moreover, this speed increase is available on consumer grade laptops, avoiding the need for a high performance computing resource.
Classification of faults in friction stir processed composites using a machine learning and ensemble learning approach
Authors: Saxena Pragya , Bongale Arunkumar
Published: October 2024

Aluminium alloy-based surface composites with hard reinforcement particles have a wide scope in the aerospace and automobile manufacturing industries. In this paper, the aluminium composites, manufactured by friction stir processing (FSP) with varying parameters are investigated for the faults that occurred during the fabrication process. In this study, Al6061 alloy surface composites reinforced with copper and graphene are fabricated using Friction Stir Processing (FSP) on a CNC milling machine. The process involves heat generation through friction, leading to a uniform distribution of reinforcement particles in the matrix. Various sensors (vibration, current, and dynamometer) are used to monitor specific parameters during the FSP experimentation. The Taguchi L27 orthogonal array is employed to design experiments for analyzing sensor data from vibration sensors, current sensors, and dynamometers during composite fabrication. Data is collected in the time domain and processed using Python libraries. Also, it explores a machine-learning approach to detect defects of surface hybrid composites with an Al6061 alloy matrix, reinforced with copper and graphene nano-powders, using friction stir processing and a tungsten carbide tool on a milling machine. Multi-sensor time series data (vibration, force, and current) collected during fabrication, is preprocessed and labelled with normal and defective categories (e.g., pin break, brazing break, rough surface, no composite) using visual inspection. The important time domain and frequency domain features are extracted using different libraries in python. Then, various types of feature selection techniques, viz filter, wrapper, and embedded methods are implemented to select the most relevant features. The selected subset of features from all selection methods used are applied to different machine learning and ensemble learning classifiers, and their performances are evaluated. The optimal combinations of the type of feature selection method and classifier used, are obtained for efficient classification of surface defects in composited formed by FSP. The impact of feature selection on classification accuracy for defect identification in FSP-fabricated composites using multisensory data is conducted. Among filter methods, the Chi-square feature selection combined with the Gradient Boosting algorithm delivers the best performance. Forward feature selection with the Random Forest classifier achieves high accuracy in wrapper methods. Additionally, the Random Forest importance selection technique paired with the Random Forest classifier provides the highest accuracy among embedded feature selection methods. The real-time monitoring and defect detection system can be developed in the future for the composites developed by FSP using the developed models.