bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesis of low-k SiONC thin films by plasma-assisted molecular layer deposition with tetraisocyanatesilane and phloroglucinol
Authors: Park Gi-Beom , Yang Hae Lin , Kim Ji Min , Jung Hyolim , Baek GeonHo , Park Chang-Kyun , Park Jin-Seong 
Published: July 2024

Abstract
Low-k SiONC thin films with excellent thermal stabilities were deposited using plasma-assisted molecular layer deposition (PA-MLD) with a tetraisocyanatesilane (Si(NCO)4) precursor, N2 plasma, and phloroglucinol (C6H3(OH)3). By adjusting the order of the N2 plasma exposure steps within the PA-MLD process, we successfully developed a deposition technique that allows accurate control of thickness at the Ångström level via self-limiting reactions. The thicknesses of the thin films were measured through spectroscopic ellipsometry (SE). By tuning the N2 plasma power, we facilitated the formation of –NH2 sites for phloroglucinol adsorption, achieving a growth per cycle of 0.18 Å cycle−1 with 300 W of N2 plasma power. Consequently, the thickness of the films increased linearly with each additional cycle. Moreover, the organic linkers within the film formed stable bonds through surface reactions, resulting in a negligible decrease in thickness of approximately −11% even upon exposure to a high annealing temperature of 600 °C. This observation was confirmed by SE, distinguishing the as-prepared film from previously reported low-k films that fail to maintain their thickness under similar conditions. X-ray photoelectron spectroscopy (XPS) and current–voltage (I–V) and capacitance–voltage (C–V) measurement were conducted to evaluate the composition, insulating properties, and dielectric constant according to the deposition and annealing conditions. XPS results revealed that as the plasma power increased from 200 to 300 W, the C/Si ratio increased from 0.37 to 0.67, decreasing the dielectric constant from 3.46 to 3.12. Furthermore, there was no significant difference in the composition before and after annealing, and the hysteresis decreased from 0.58 to 0.19 V owing to defect healing, while maintaining the leakage current density, breakdown field, and dielectric constant. The low dielectric constant, accurate thickness control, and excellent thermal stability of this MLD SiONC thin film enable its application as an interlayer dielectric in back-end-of-line process.
An experimental validation of a filtering approach for prompt gamma prediction in a research proton treatment planning system
Authors: Huang Ze , Tian Liheng , Janssens Guillaume , Smeets Julien , Xie Yunhe , Kevin Teo Boon-Keng , Nilsson Rasmus , Traneus Erik , Parodi Katia , Pinto Marco 
Published: July 2024

Abstract

Objective. Prompt gamma (PG) radiation generated from nuclear reactions between protons and tissue nuclei can be employed for range verification in proton therapy. A typical clinical workflow for PG range verification compares the detected PG profile with a predicted one. Recently, a novel analytical PG prediction algorithm based on the so-called filtering formalism has been proposed and implemented in a research version of RayStation (RaySearch Laboratories AB), which is a widely adopted treatment planning system. This work validates the performance of the filtering PG prediction approach. Approach. The said algorithm is validated against experimental data and benchmarked with another well-established PG prediction algorithm implemented in a MATLAB-based software REGGUI. Furthermore, a new workflow based on several PG profile quality criteria and analytical methods is proposed for data selection. The workflow also calculates sensitivity and specificity information, which can help practitioners to decide on irradiation course interruption during treatment and monitor spot selection at the treatment planning stage. With the proposed workflow, the comparison can be performed on a limited number of selected high-quality irradiation spots without neighbouring-spot aggregation. Main results. The mean shifts between the experimental data and the predicted PG detection (PGD) profiles (ΔPGD) by the two algorithms are estimated to be

1.5
±
2.1

mm and

−
0.6
±
2.2

mm for the filtering and REGGUI prediction methods, respectively. The ΔPGD difference between two algorithms is observed to be consistent with the beam model difference within uncertainty. However, the filtering approach requires a much shorter computation time compared to the REGGUI approach. Significance. The novel filtering approach is successfully validated against experimental data and another widely used PG prediction algorithm. The workflow designed in this work selects spots with high-quality PGD shift calculation results, and performs sensitivity and specificity analyses to assist clinical decisions.
Joint diffusion: mutual consistency-driven diffusion model for PET-MRI co-reconstruction
Authors: Xie Taofeng , Cui Zhuo-Xu , Luo Chen , Wang Huayu , Liu Congcong , Zhang Yuanzhi , Wang Xuemei , Zhu Yanjie , Chen Guoqing , Liang Dong , Jin Qiyu , Zhou Yihang , Wang Haifeng 
Published: July 2024

Abstract

Objective. Positron Emission Tomography and Magnetic Resonance Imaging (PET-MRI) systems can obtain functional and anatomical scans. But PET suffers from a low signal-to-noise ratio, while MRI are time-consuming. To address time-consuming, an effective strategy involves reducing k-space data collection, albeit at the cost of lowering image quality. This study aims to leverage the inherent complementarity within PET-MRI data to enhance the image quality of PET-MRI. Approach. A novel PET-MRI joint reconstruction model, termed MC-Diffusion, is proposed in the Bayesian framework. The joint reconstruction problem is transformed into a joint regularization problem, where data fidelity terms of PET and MRI are expressed independently. The regular term, the derivative of the logarithm of the joint probability distribution of PET and MRI, employs a joint score-based diffusion model for learning. The diffusion model involves the forward diffusion process and the reverse diffusion process. The forward diffusion process adds noise to transform a complex joint data distribution into a known joint prior distribution for PET and MRI simultaneously, resembling a denoiser. The reverse diffusion process removes noise using a denoiser to revert the joint prior distribution to the original joint data distribution, effectively utilizing joint probability distribution to describe the correlations of PET and MRI for improved quality of joint reconstruction. Main results. Qualitative and quantitative improvements are observed with the MC-Diffusion model. Comparative analysis against LPLS and Joint ISAT-net on the ADNI dataset demonstrates superior performance by exploiting complementary information between PET and MRI. The MC-Diffusion model effectively enhances the quality of PET and MRI images. Significance. This study employs the MC-Diffusion model to enhance the quality of PET-MRI images by integrating the fundamental principles of PET and MRI modalities and leveraging their inherent complementarity. Furthermore, utilizing the diffusion model to learn the joint probability distribution of PET and MRI, thereby elucidating their latent correlation, facilitates a more profound comprehension of the priors obtained through deep learning, contrasting with black-box prior or artificially constructed structural similarities.
A nonparametric measure of contrast in x-ray images
Authors: Anton M , Reginatto M , Schopphoven S , Abou Jaoude C , Mäder U , Fiebich M , Mauter F , Sechopoulos I , van Engen R 
Published: July 2024

Abstract

Objective. We propose a nonparametric figure of merit, the contrast equivalent distance CED, to measure contrast directly from clinical images. Approach. A relative brightness distance δ is calculated by making use of the order statistic of the pixel values. By multiplying δ with the grey value range R, the mean brightness distance MBD is obtained. From the MBD, the CED and the distance-to-noise ratio DNR can be derived. The latter is the ratio of the MBD and a previously suggested nonparametric measure τ for the noise.
Since the order statistic is independent of the spatial arrangement of the pixel values, the measures can be obtained directly from clinical images. We apply the new measures to mammography images of an anthropomorphic phantom and of a phantom with a step wedge as well as to CT images of a head phantom. Main results. For low-noise images of a step wedge, the MBD is equivalent to the conventional grey value distance. While this measure permits the evaluation of clinical images, it is sensitive to noise. Therefore, noise has to be quantified at the same time. When the ratio

σ

/

τ

of the noise standard deviation σ to τ is available, validity limits for the CED as a measure of contrast can be established. The new figures of merit can be calculated for entire images as well as on regions of interest (ROI) with an edge length not smaller than 32 px.
Significance. The new figures of merit are suited to quantify the quality of clinical images without relying on the assumption of a linear, shift-invariant system. They can be used for any kind of greyscale image, provided the ratio

σ

/

τ

can be estimated. This will hopefully help to achieve the optimisation of image quality vs dose required by radioprotection laws.
Bifurcation detection in intravascular optical coherence tomography using vision transformer based deep learning
Authors: Zhu Rongyang , Li Qingrui , Ding Zhenyang , Liu Kun , Lin Qiutong , Yu Yin , Li Yuanyao , Zhou Shanshan , Kuang Hao , Jiang Junfeng , Liu Tiegen 
Published: July 2024

Abstract

Objective. Bifurcation detection in intravascular optical coherence tomography (IVOCT) images plays a significant role in guiding optimal revascularization strategies for percutaneous coronary intervention (PCI). We propose a bifurcation detection method using vision transformer (ViT) based deep learning in IVOCT. Approach. Instead of relying on lumen segmentation, the proposed method identifies the bifurcation image using a ViT-based classification model and then estimate bifurcation ostium points by a ViT-based landmark detection model. Main results. By processing 8640 clinical images, the Accuracy and F1-score of bifurcation identification by the proposed ViT-based model are 2.54% and 16.08% higher than that of traditional non-deep learning methods, are similar to the best performance of convolutional neural networks (CNNs) based methods, respectively. The ostium distance error of the ViT-based model is 0.305 mm, which is reduced 68.5% compared with the traditional non-deep learning method and reduced 24.81% compared with the best performance of CNNs based methods. The results also show that the proposed ViT-based method achieves the highest success detection rate are 11.3% and 29.2% higher than the non-deep learning method, and 4.6% and 2.5% higher than the best performance of CNNs based methods when the distance section is 0.1 and 0.2 mm, respectively. Significance. The proposed ViT-based method enhances the performance of bifurcation detection of IVOCT images, which maintains a high correlation and consistency between the automatic detection results and the expert manual results. It is of great significance in guiding the selection of PCI treatment strategies.
A novel MTCMOS based 8T2M NVSRAM design for low power applications with high temperature endurance
Authors: Chakraborty Udayan , Majumder Tanmoy , Debbarma Rupanjal , Das Narottam , Bhattacharjee Abhishek 
Published: July 2024

AbstractThis research investigates, for the first time, a novel eight-transistor-two-memristor (8T2M) nonvolatile static random access memory (NVSRAM) with 7-nm technology. The key innovation in this design lies in the incorporation of multiple-threshold complementary metal oxide semiconductor (MTCMOS) technology with power gating technique, which enables efficient power management and enhanced performance with low leakage current. The implementation of multiple threshold voltage levels allows for dynamic control of transistor behavior, optimizing power consumption and read/write speeds. As compared to a traditional six-transistor (6T) static random access memory (SRAM) cell, it has been ascertained that there is a 33% enhancement in the read margin and an 18% improvement in the write margin. Moreover, the delay for read, write ‘0’ and write ‘1’ is also minimized by 63.89%, 37.99% and 42.77%. Furthermore, the power attenuation is also reduced for read and write by 63.02% and 81.6%, respectively with respect to a conventional SRAM.
Comparative study of the electronic and optical properties of Rhenium based Chalcogenides
Authors: Banik Diparnab , Lionel Chrislene , Das Shubham , Koley S 
Published: July 2024

Abstract
Transition metal dichalcogenides are materials of growing interest due to their unique electronic properties and rich phase diagram, offering promising opportunities for various applications. In this study, we investigate the optoelectronic characteristics of two-dimensional rhenium (Re)-based chalcogenides. These materials are composed of rhenium atoms sandwiched between chalcogen layers. In this paper, we have selected three rhenium-based chalcogenide (ReS2, ReSe2 and ReTe2) compounds in their 1T structure and calculated their electronic properties. Our study aims to find the intricacies of theoretical band structures and optical properties, aiming to assess their viability as semiconducting materials for the optoelectronics industry employing density funtional theory. Furthermore, we explore the impact of varying chalcogen compositions on the optoelectronic behavior, uncovering the tunability of these materials for specific applications. The study provides insights into the role of Re-based chalcogenides as promising candidates for emerging technologies, including photodetectors, solar cells, and other optoelectronic devices. The observed band gaps highlight the potential of these materials within the infrared region of the electromagnetic spectrum. After observing optical properties derived from our calculations, we discuss the corresponding potentials of the chosen materials in optoelectronic applications.
Spin–orbit torque effect in silicon-based sputtered Mn3Sn film
Authors: Lu 卢 Sha 莎 , Meng 孟 Dequan 德全 , Khan Adnan , Wang 王 Ziao 子傲 , Chen 陈 Shiwei 是位 , Liang 梁 Shiheng 世恒 
Published: July 2024

Abstract
Noncollinear antiferromagnet Mn3Sn has shown remarkable efficiency in charge–spin conversion, a novel magnetic spin Hall effect, and a stable topological antiferromagnetic state, which has resulted in great interest from researchers in the field of spin–orbit torque. Current research has primarily focused on the spin–orbit torque effect of epitaxially grown noncollinear antiferromagnet Mn3Sn films. However, this method is not suitable for large-scale industrial preparation. In this study, amorphous Mn3Sn films and Mn3Sn/Py heterostructures were prepared using magnetron sputtering on silicon substrates. The spin-torque ferromagnetic resonance measurement demonstrated that only the conventional spin–orbit torque effect generated by in-plane polarized spin currents existed in the Mn3Sn/Py heterostructure, with a spin–orbit torque efficiency of 0.016. Additionally, we prepared the perpendicular magnetized Mn3Sn/CoTb heterostructure based on amorphous Mn3Sn film, where the spin–orbit torque driven perpendicular magnetization switching was achieved with a lower critical switching current density (3.9×107 A/cm2) compared to Ta/CoTb heterostructure. This research reveals the spin–orbit torque effect of amorphous Mn3Sn films and establishes a foundation for further advancement in the practical application of Mn3Sn materials in spintronic devices.
A systematic review of fall prediction models for community-dwelling older adults: comparison between models based on research cohorts and models based on routinely collected data
Authors: Dormosh Noman , van de Loo Bob , Heymans Martijn W , Schut Martijn C , Medlock Stephanie , van Schoor Natasja M , van der Velde Nathalie , Abu-Hanna Ameen 
Published: July 2024

Abstract

Background
Prediction models can identify fall-prone individuals. Prediction models can be based on either data from research cohorts (cohort-based) or routinely collected data (RCD-based). We review and compare cohort-based and RCD-based studies describing the development and/or validation of fall prediction models for community-dwelling older adults.

Methods
Medline and Embase were searched via Ovid until January 2023. We included studies describing the development or validation of multivariable prediction models of falls in older adults (60+). Both risk of bias and reporting quality were assessed using the PROBAST and TRIPOD, respectively.

Results
We included and reviewed 28 relevant studies, describing 30 prediction models (23 cohort-based and 7 RCD-based), and external validation of two existing models (one cohort-based and one RCD-based). The median sample sizes for cohort-based and RCD-based studies were 1365 [interquartile range (IQR) 426–2766] versus 90 441 (IQR 56 442–128 157), and the ranges of fall rates were 5.4% to 60.4% versus 1.6% to 13.1%, respectively. Discrimination performance was comparable between cohort-based and RCD-based models, with the respective area under the receiver operating characteristic curves ranging from 0.65 to 0.88 versus 0.71 to 0.81. The median number of predictors in cohort-based final models was 6 (IQR 5–11); for RCD-based models, it was 16 (IQR 11–26). All but one cohort-based model had high bias risks, primarily due to deficiencies in statistical analysis and outcome determination.

Conclusions
Cohort-based models to predict falls in older adults in the community are plentiful. RCD-based models are yet in their infancy but provide comparable predictive performance with no additional data collection efforts. Future studies should focus on methodological and reporting quality.
Full employment as a condition of crisis: Kalecki’s Marxian critique of Keynes and the Fabians (1942–45)
Authors: Lampa Roberto 
Published: July 2024

Abstract
Between 1942 and 1945, Kalecki emphasised the incompatibility between capitalism and full employment. Rather than stabilising market economies, full employment would have triggered social conflict by providing self-confidence amongst the workers and the lower strata of society. Accordingly, in any program of social transformation, the initial condition that had to be established was (guaranteed) full employment and economic security for workers to alter the game’s rules. Like Marx, full employment of resources became a condition of crisis in a capitalist economy. Upon this premise, Kalecki rejected both Keynes’s and the Fabians’ views, according to which full employment was essentially a technical operation to be achieved by intellectual persuasion and some basic control. The emphasis on persuasion implied an overestimation of the role of economic theory, meant as a method of moulding ideas and opinions of the country leaders. On the other hand, the lack of institutional analysis implied that full employment became a mere tool to guarantee capitalism’s correct functioning. Kalecki’s stance reflected his different background, both methodological and political.
Relation Between the Dantu Blood Group Variant and Bacteremia in Kenyan Children: A Population-Based Case-Control Study
Authors: Kariuki Silvia N , Gilchrist James J , Uyoga Sophie , Macharia Alexander , Makale Johnstone , Rayner Julian C , Williams Thomas N 
Published: July 2024

Abstract

Background
The Dantu blood group variant protects against Plasmodium falciparum infections, but its wider consequences have not been previously explored. Here, we investigate the impact of Dantu on susceptibility to bacteremia.

Methods
We conducted a case-control study in children presenting with community-acquired bacteremia to Kilifi County Hospital in Kenya between 1998 and 2010. We used logistic regression to test for associations between the Dantu marker single-nucleotide polymorphism rs186873296 A &gt; G and both all-cause and pathogen-specific bacteremia under an additive model. We used date of admission as a proxy measure of malaria transmission intensity, given known differences in malaria prevalence over the course of the study.

Results
Dantu was associated with protection from all-cause bacteremia (OR, 0.81; P = .014), the association being greatest in homozygotes (OR, 0.30; P = .013). This protection was shared across the major bacterial pathogens but, notably, was only significant during the era of high malaria transmission pre-2003 (OR, 0.79; P = .023).

Conclusions
Consistent with previous studies showing the indirect impact on bacteremia risk of other malaria-associated red cell variants, our study also shows that Dantu is protective against bacteremia via its effect on malaria risk. Dantu does not appear to be under balancing selection through an increased risk of bacterial infections.
Fragmentation of dense rotation-dominated structures fed by collapsing gravo-magneto-sheetlets and origin of misaligned 100 au-scale binaries and multiple systems
Authors: Tu Yisheng , Li Zhi-Yun , Zhu Zhaohuan , Hsu Chun-Yen 
Published: July 2024

ABSTRACT
The majority of stars are in binary/multiple systems. How such systems form in turbulent, magnetized cores of molecular clouds in the presence of non-ideal magnetohydrodynamic (MHD) effects remains relatively underexplored. Through athena++-based non-ideal MHD adaptive mesh refinement simulations with ambipolar diffusion, we show that the collapsing protostellar envelope is dominated by dense gravo-magneto-sheetlets, a turbulence-warped version of the classic pseudodisc produced by anisotropic magnetic resistance to the gravitational collapse, in agreement with previous simulations of turbulent, magnetized single-star formation. The sheetlets feed mass, magnetic fields, and angular momentum to a Dense ROtation-Dominated (DROD) structure, which fragments into binary/multiple systems. This DROD fragmentation scenario is a more dynamic variant of the traditional disc fragmentation scenario for binary/multiple formation, with dense spiral filaments created by inhomogeneous feeding from the highly structured larger-scale sheetlets rather than the need for angular momentum transport, which is dominated by magnetic braking. Provided that the local material is sufficiently demagnetized, with a plasma-$\beta$ of 10 or more, collisions between the dense spiralling filaments play a key role in facilitating gravitational collapse and stellar companion formation by pushing the local magnetic Toomre parameter $Q_\mathrm{m}$ below unity. This mechanism can naturally produce in situ misaligned systems on the 100-au scale, often detected with high-resolution Atacama Large Millimeter Array (ALMA) observations. Our simulations also highlight the importance of non-ideal MHD effects, which affect whether fragmentation occurs and, if so, the masses and orbital parameters of the stellar companions formed.