bluuebunny/crossref_metadata_2025_split huggingface dataset:
Radially symmetric stationary solutions for a MEMS type reaction–diffusion equation with fringing field
Authors: Ichida Yu , Sakamoto Takashi Okuda 
Published: November 2022

Abstract
Radially symmetric stationary solutions for a micro-electro-mechanical system (MEMS) type reaction–diffusion equation with fringing field are considered. This equation arises in the study of the MEMS devices. This paper is devoted to the study of the existence of these solutions, information about their shape, and their asymptotic behaviour. These are studied by applying the framework that combines Poincaré type compactification, classical dynamical systems theory, and geometric methods for desingularization of vector fields called the blow-up technique.
Helicity, linking and the distribution of null-homologous periodic orbits for Anosov flows*
Authors: Coles Solly , Sharp Richard 
Published: November 2022

Abstract
This paper concerns connections between dynamical systems, knots and helicity of vector fields. For a divergence-free vector field on a closed three-manifold that generates an Anosov flow, we show that the helicity of the vector field may be recovered as the limit of appropriately weighted averages of linking numbers of periodic orbits, regarded as knots. This complements a classical result of Arnold and Vogel that, when the manifold is a real homology three-sphere, the helicity may be obtained as the limit of the normalised linking numbers of typical pairs of long trajectories. We also obtain results on the asymptotic distribution of weighted averages of null-homologous periodic orbits.
A multi-perspective information aggregation network for automated T-staging detection of nasopharyngeal carcinoma
Authors: Liang Shujun , Dong Xiuyu , Yang Kaifan , Chu Zhiqin , Tang Fan , Ye Feng , Chen Bei , Guan Jian , Zhang Yu 
Published: November 2022

Abstract
Accurate T-staging is important when planning personalized radiotherapy. However, T-staging via manual slice-by-slice inspection is time-consuming while tumor sizes and shapes are heterogeneous, and junior physicians find such inspection challenging. With inspiration from oncological diagnostics, we developed a multi-perspective aggregation network that incorporated various diagnosis-oriented knowledge which allowed automated nasopharyngeal carcinoma T-staging detection (TSD Net). Specifically, our TSD Net was designed in multi-branch architecture, which can capture tumor size and shape information (basic knowledge), strongly correlated contextual features, and associations between the tumor and surrounding tissues. We defined the association between the tumor and surrounding tissues by a signed distance map which can embed points and tumor contours in higher-dimensional spaces, yielding valuable information regarding the locations of tissue associations. TSD Net finally outputs a T1–T4 stage prediction by aggregating data from the three branches. We evaluated TSD Net by using the T1-weighted contrast-enhanced magnetic resonance imaging database of 320 patients in a three-fold cross-validation manner. The results show that the proposed method achieves a mean area under the curve (AUC) as high as 87.95%. We also compared our method to traditional classifiers and a deep learning-based method. Our TSD Net is efficient and accurate and outperforms other methods.
A synthetic phase-contrast imaging diagnostic with spatial filtering for gyrokinetic simulations
Authors: Iantchenko A , Coda S , Brunner S , Merlo G , Ball J , Margairaz F 
Published: November 2022

Abstract
A Phase-contrast imaging (PCI) diagnostic provides measurements of line-integrated electron density fluctuations. Localisation along the laser beam path can be achieved with a spatial filter that selects the wave-vector directions of the fluctuations contributing to the PCI measurement and is a key feature of the PCI diagnostic installed on the TCV tokamak and also of a similar system planned for JT-60SA. We have developed a synthetic diagnostic that models measurements from PCI taking into account the effect of such a spatial filter. The synthetic tool is based on the principle of integrating over selected diagnostic volumes the electron density fluctuations generated by turbulence simulations, and applying an appropriate spatial filter in wave-vector space. We demonstrate the effect of the filter for a positive and a negative triangularity TCV discharge, and illustrate the potential of the synthetic diagnostic for better understanding the corresponding experimental results. We consider different types of filters and make first-principle estimates of the localisation of the measurement. Finally, using gyrokinetic simulations that include electromagnetic effects, collisions and four kinetic species, we make first predictions of the characteristics of the measurements using the planned set-up of PCI on JT-60SA.
Revisiting Riemannian geometry-based EEG decoding through approximate joint diagonalization
Authors: Kalaganis Fotis P , Laskaris Nikos A , Oikonomou Vangelis P , Nikopolopoulos Spiros , Kompatsiaris Ioannis 
Published: November 2022

Abstract

Objective. The wider adoption of Riemannian geometry in electroencephalography (EEG) processing is hindered by two factors: (a) it involves the manipulation of complex mathematical formulations and, (b) it leads to computationally demanding tasks. The main scope of this work is to simplify particular notions of Riemannian geometry and provide an efficient and comprehensible scheme for neuroscientific explorations. Approach. To overcome the aforementioned shortcomings, we exploit the concept of approximate joint diagonalization in order to reconstruct the spatial covariance matrices assuming the existence of (and identifying) a common eigenspace in which the application of Riemannian geometry is significantly simplified. Main results. The employed reconstruction process abides to physiologically plausible assumptions, reduces the computational complexity in Riemannian geometry schemes and bridges the gap between rigorous mathematical procedures and computational neuroscience. Our approach is both formally established and experimentally validated by employing real and synthetic EEG data. Significance. The implications of the introduced reconstruction process are highlighted by reformulating and re-introducing two signal processing methodologies, namely the ‘Symmetric Positive Definite (SPD) Matrix Quantization’ and the ‘Coding over SPD Atoms’. The presented approach paves the way for robust and efficient neuroscientific explorations that exploit Riemannian geometry schemes.
Energetic particle optimization of quasi-axisymmetric stellarator equilibria
Authors: LeViness Alexandra , Schmitt John C. , Lazerson Samuel A. , Bader Aaron , Faber Benjamin J. , Hammond Kenneth C. , Gates David A. 
Published: November 2022

Abstract
An important goal of stellarator optimization is to achieve good confinement of energetic particles such as, in the case of a reactor, alphas created by deuterium–tritium fusion. In this work, a fixed-boundary stellarator equilibrium was re-optimized for energetic particle confinement via a two-step process: first, by minimizing deviations from quasi-axisymmetry (QA) on a single flux surface near the mid-radius, and secondly by maintaining this improved QA while minimizing the analytical quantity

Γ

C

, which represents the angle between magnetic flux surfaces and contours of

J

|

|

, the second adiabatic invariant. This was performed multiple times, resulting in a group of equilibria with significantly reduced energetic particle losses, as evaluated by Monte Carlo simulations of alpha particles in scaled-up versions of the equilibria. This is the first time that energetic particle losses in a QA stellarator have successfully been reduced by optimizing

Γ

C

. The relationship between energetic particle losses and metrics such as QA error (

E

q
a

) and

Γ

C

in this set of equilibria were examined via statistical methods and a nearly linear relationship between volume-averaged

Γ

C

and prompt particle losses was found.
Size-dependent molecular interaction of nontraditional 2D antibiotics with Staphylococcus aureus
Authors: Najafi F , Ahmadi H , Maghsoumi A , Huma K , Amini A , Azimi L , Karimi A , Bayat M , Naseri N 
Published: November 2022

Abstract
The application of nanomaterials for their antibacterial properties is the subject of many studies due to antibiotic resistance of pathogen bacteria and the necessity of omitting them from food and water resources. Graphene oxide (GO) is one of the most popular candidates for antibacterial application. However, the optimum condition for such an effect is not yet clear for practical purposes. To shed light on how GO and bacteria interaction depends on size, a wide range of GO flake sizes from hundreds of µm2 going down to nano-scale as low as 10 N m2 was produced. In an in-vitro systematic study to inhibit Staphylococcus aureus growth, the correlation between GO flake size, thickness, functional group density, and antibacterial activity was investigated. The GO suspension with the average size of 0.05 µm2, in the order of the size of the bacteria itself, had the best bacteriostatic effect on S. aureus with the minimum inhibitory concentration value of 8 μg ml−1, well within the acceptable range for practical use. The bacteriostatic effect was measured to be a 76.2% reduction of the colony count over 2 h of incubation and the mechanism of action was the wrapping and isolation of cells from the growth environment. Furthermore, in-vivo animal studies revealed that 16 μg ml−1 of the optimum GO has efficient antibacterial performance against the methicillin-resistant strains of the bacteria with an enhanced wound healing rate and tensiometrial parameters which is important for realized targets.
Critical mineral constraints in global renewable scenarios under 1.5 °C target
Authors: Wang Peng , Chen Wei-Qiang , Cui Xueqin , Li Jiashuo , Li Wen , Wang Chenyang , Cai Wenjia , Geng Xinyi 
Published: November 2022

Abstract
To avoid catastrophic climate change, the world is promoting a fast and unprecedented transition from fuels to renewables. However, the infrastructures of renewables, such as wind turbines and solar cells, rely heavily on critical minerals like rare earths, indium, etc. Such interactions between climate targets, energy transitions, and critical minerals were widely overlooked in the present climate scenario analysis. This study aims to fill this gap through an introduction of metal–energy–climate nexus framework with its application on global energy transition towards a carbon-neutral (or below 1.5 °C) target, in which six state-of-the-art integrated assessment models (IAMs) under different shared socioeconomic pathways were applied. Our analysis revealed that climate mitigation is expected to boost significantly the critical mineral demand by 2.6–267-fold, which varies greatly by IAM models. Solar power development may be constrained by tellurium (Te) and selenium (Se) shortage, while wind power will be jeopardized by the limited scalability of rare earth production. Moreover, a more sustainable pathway may come at higher demand for critical minerals along with higher renewable ratios. Consequently, a holistic investigation of the interaction of mineral, energy, and climate systems is highly recommended for future scenario designing.
Modeling of magnetized collisional plasma sheath with nonextensive electron distribution and ionization source
Authors: CHEN Long , YANG Yehui , AN Yuhao , DUAN Ping , SUN Shaojuan , CUI Zuojun , KAN Zichen , GAO Weifu 
Published: November 2022

Abstract
The properties of an atmospheric-pressure collisional plasma sheath with nonextensively distributed electrons and hypothetical ionization source terms are studied in this work. The Bohm criterion for the magnetized plasma is extended in the presence of an ion–neutral collisional force and ionization source. The effects of electron nonextensive distribution, ionization frequency, ion–neutral collision, magnetic field angle and ion temperature on the Bohm criterion of the plasma sheath are numerically analyzed. The fluid equations are solved numerically in the plasma–wall transition region using a modified Bohm criterion as the boundary condition. The plasma sheath properties such as charged particle density, floating sheath potential and thickness are thoroughly investigated under different kinds of ion source terms, contributions of collisions, and magnetic fields. The results show that the effect of the ion source term on the properties of atmospheric-pressure collisional plasma sheath is significant. As the ionization frequency increases, the Mach number of the Bohm criterion decreases and the range of possible values narrows. When the ion source is considered, the space charge density increases, the sheath potential drops more rapidly, and the sheath thickness becomes narrower. In addition, ion–neutral collision, magnetic field angle and ion temperature also significantly affect the sheath potential profile and sheath thickness.
Functional disability trajectories at the end of life among Japanese older adults: findings from the Japan Gerontological Evaluation Study (JAGES)
Authors: Saito Junko , Murayama Hiroshi , Ueno Takayuki , Saito Masashige , Haseda Maho , Saito Tami , Kondo Katsunori , Kondo Naoki 
Published: November 2022

AbstractBackgroundthis study aimed to identify distinct subgroups of trajectories of disability over time before 3 years of death and examine the factors associated with trajectory group membership probabilities among community-dwelling Japanese older adults aged 65 years and above.Methodsparticipants included 4,875 decedents from among community-dwelling Japanese older adults, aged ≥ 65 years at baseline (men: 3,020; women: 1,855). The certified long-term care levels of the national long-term care insurance (LTCI) system were used as an index of functional disability. We combined data from the 2010 Japan Gerontological Evaluation Study and data from the 2010 to 2016 LTCI system. Group-based mixture models and multinominal logistic regression models were used for data analysis.Resultsfive distinct trajectories of functional disability in the last 3 years of life were identified: ‘persistently severe disability’ (10.3%), ‘persistently mild disability’ (13.0%), ‘accelerated disability’ (12.6%), ‘catastrophic disability’ (18.8%) and ‘minimum disability’ (45.2%). Multinominal logistic regression analysis found several factors associated with trajectory membership; self-rated health was a common predictor regardless of age and gender. The analysis also showed a paradoxical association; higher education was associated with trajectory group membership probabilities of more severe functional decline in men over 85 years at death.Conclusionsindividual perception of health was a strong predictor of trajectories, independent of demographic factors and socio-economic status. Our findings contribute to the development of policies for the long-term care system, particularly for end-of-life care, in Asian countries.
Association of impaired lung function with dementia, and brain magnetic resonance imaging indices: a large population-based longitudinal study
Authors: Zhou Lihui , Yang Hongxi , Zhang Yuan , Li Huiping , Zhang Shunming , Li Dun , Ma Yue , Hou Yabing , Lu Wenli , Wang Yaogang 
Published: November 2022

AbstractObjectiveto examine the association between different patterns of impaired lung function with the incident risk of dementia and magnetic resonance imaging (MRI)-based brain structural features.Methodsin UK Biobank, a total of 308,534 dementia-free participants with valid lung function measures (forced expiratory volume in 1 s [FEV1] and forced vital capacity [FVC]) were included. Association was assessed using Cox proportional hazards regression model. Furthermore, the association between impaired lung function and brain MRI biomarkers related to cognitive function was analysed among 30,159 participants.Resultsduring a median follow-up of 12.6 years, 3,607 incident all-cause dementia cases were recorded. Restrictive impairment (hazard ratio [HR], 1.42; 95% confidence interval [CI], 1.27–1.60) and obstructive impairment (HR, 1.28; 95% CI, 1.15–1.42) were associated with higher risk of all-cause dementia. The restricted cubic splines indicated FEV1% predicted and FVC % predicted had reversed J-shaped associations with dementia. Participants with impaired lung function have higher risks of all-cause dementia across all apolipoprotein E (APOE) risk categories, whereas associations were stronger among those of low APOE risk (P for interaction = 0.034). In addition, restrictive and obstructive impairment were linked to lower total (β: −0.075, SE: 0.021, Pfdr = 0.002; β: −0.033, SE: 0.017, Pfdr = 0.069) and frontoparietal grey matter volumes, higher white matter hyperintensity, poorer white matter integrity, lower hippocampus (β: –0.066, SE: 0.024, Pfdr = 0.017; β: –0.051, SE: 0.019, Pfdr = 0.019) and other subcortical volumes.Conclusionsparticipants with restrictive and obstructive impairments had a higher risk of dementia. Brain MRI indices further supported adverse effects and provided insight into potential pathophysiology biomarkers.
Law as Peace (Or Why I Am Still a Hard-Core Positivist)
Authors: Kletzer Christoph 
Published: November 2022

Abstract
The fact that the most prominent brands of positivism and natural law theory, namely their Razian and Finnisian variants, are in agreement about some hitherto hotly contested issues has over the decades become more of an entertaining curio than an actual concern that ruffles any theoretical feathers. Whatever its benefits, this great convergence requires positivism to forfeit much of what has originally made it a theoretically appealing position. One of the many reasons for the curious alignment of positivism with natural law theory has been a focus on the explanatory power and theoretical import of the phenomenon of friendship. If we allow the countervailing forces of enmity to be given their due weight, a different model of law emerges, namely law as peace, which is more resistant to the contortions and ultimate self-abandonment that ensues from the alignment of positivism with natural law theory.
Patient-Reported Outcomes After Reduction Mammoplasty Using BREAST-Q: A Systematic Review and Meta-Analysis
Authors: Wang Alice T , Panayi Adriana C , Fischer Sebastian , Diehm Yannick F , Tapking Christian , Hundeshagen Gabriel , Kneser Ulrich , Mastroianni Melissa , Pomahac Bohdan , Haug Valentin 
Published: November 2022

Abstract

Background
The BREAST-Q questionnaire reduction module is an established tool for outcomes after reduction mammoplasty.

Objectives
This systematic review and meta-analysis assess key parameters affecting pre- and postoperative scores, with specific foci on patient characteristics and tissue resection weights.

Methods
This study was conducted per PRISMA guidelines. PUBMED (National Institutes of Health; Bethesda, MD), Google Scholar (Google; Mountain View, CA), and Web of Science (Clarivate Analytics; Philadelphia, PA) were searched. All studies published before August 1, 2021, were assessed for eligibility by 2 independent reviewers. Inclusion criteria were prospective or retrospective studies in 6 languages that reported quality of life after reduction mammoplasty employing the BREAST-Q questionnaire reduction module. Quality of included studies was assessed employing the Newcastle-Ottawa-Scale. Analysis was performed per Cochrane Collaboration and the Quality of Reporting of Meta-analyses guidelines.

Results
A total of 28 papers were included in the systematic review, 13 for preoperative meta-analysis, and 17 for postoperative meta-analysis. Postoperative scores in all 3 quality of life domains (psychosocial, physical, and sexual well-being) and satisfaction with breasts increased significantly after reduction mammoplasty compared with preoperative scores. Satisfaction with breasts showed the greatest improvement, from 22.9 to 73.0. Preoperative scores were lower than normative data, with improvement to comparable scores as the healthy population postoperatively. Improvements in BREAST-Q scores did not correlate with patient comorbidities, complication rates, or amount of breast tissue resected.

Conclusions
Reduction mammoplasty provides marked improvement in BREAST-Q patient-reported quality of life as well established in literature. However, these improvements do not correlate with tissue resection weights, warranting further inquiry of insurance-defined resection requirements.

Level of Evidence: 3
Effect of chronic exposure to ketohexoses on pancreatic β-cell function in INS-1 rat insulinoma cells
Authors: Kohara Yuri , Ikai Shuta , Yoshihara Akihide , Murao Koji , Sugiyama Yasunori 
Published: November 2022

ABSTRACT
Glucotoxicity, impaired insulin secretion, suppression of insulin gene expression, and apoptosis, in pancreatic β-cells caused by chronic hyperglycemia is a key component of the pathogenesis of type 2 diabetes. Recently, it has been reported that rare sugar d-allulose has antihyperglycemic and antihyperlipidemic effects in diabetic rats. However, the direct effects of rare sugars including d-allulose on pancreatic β-cell function are unclear. In this study, we investigated whether chronic exposure to ketohexoses causes glucotoxicity, suppression of insulin gene expression, and apoptosis, in INS-1 rat pancreatic insulinoma cells. d-Fructose, d-tagatose, l-allulose, and l-sorbose treatment for 1-week reduced insulin gene expression, whereas d-allulose, d-sorbose, l-fructose, and l-tagatose did not. All ketohexoses were transported into INS-1 cells, but were not metabolized. In addition, the ketohexoses did not induce apoptosis and did not affect glucose metabolism. These results suggest that long-term administration of d-allulose, d-sorbose, l-fructose, and l-tagatose does not affect pancreatic β-cell function.
Range shift and loss of genetic diversity under climate change in the red-backed fairywren (Malurus melanocephalus), an Australian endemic bird species
Authors: Perktaş Utku 
Published: November 2022

AbstractClimatic variability is the most important force influencing the distribution dynamics of common and widespread species, with significant effects on their current biogeographical patterns. In this study, phylogeography was integrated with ecological niche modelling to understand the range dynamics of an Australian bird species, the red-backed fairywren (Malurus melanocephalus), under various climate change scenarios. Specifically, an ecological niche modelling approach with Bayesian-based phylogeographical analysis was used to develop robust inferences regarding the demographic history of the species. The predictions of the model were mostly consistent with the present distribution of the species. However, under the Last Interglacial bioclimatic conditions, the model predicted a significantly narrower distribution than today, indicating the existence of allopatric refugia. Predictions for the Last Glacial Maximum indicated that the species had a wider distribution, extending northwards. Additionally, predictions for the future (2050 and 2070) indicated that the species will probably have a narrower distribution than at present, which will be shifted eastwards. The extended Bayesian skyline plot analysis, which provides a robust analysis of fluctuations in the effective population size throughout the evolutionary history of a species, produced results highly consistent with the ecological niche modelling predictions for the red-backed fairywren. This is the first study to investigate the Late Quaternary history of an endemic avian taxon from Australia using ecological niche modelling and Bayesian-based demographic analysis.