bluuebunny/crossref_metadata_2025_split huggingface dataset:
One-step hydrothermal preparation of corrosion-resistant coatings with microsphere structure
Authors: Chen Shengli , Zhu Jiyuan 
Published: April 2024

Abstract
Rapid corrosion rate is limiting the engineering application of magnesium alloys. In this paper, an attempt was made to produce a corrosion resistant coating on the surface of AZ91D magnesium alloy using hydrothermal method. The coating surface is covered with microspheres and has a dense structure, which effectively isolates the contact between the outside world and the substrate. The corrosion potential(E) raised from −1.57 V to −0.45 V compared to the bare sample. The corrosion current density and corrosion rate of the coating can be reduced by 6 orders of magnitude, and the polarization resistance raised by 6 orders of magnitude. The thickness of the coating is 45.4 μm at the moment, with a minimum of defects on the surface, resulting in excellent corrosion resistance in the immersion test. The coating also has good adhesion strength at 4B, which can expand the application range of magnesium alloy in corrosive environments.
Comparative assessment of supervised machine learning algorithms for predicting geometric characteristics of laser cladded inconel 718
Authors: Yang Hao , Geng Heran , Alfano Marco , Yuan Junfeng 
Published: April 2024

Abstract
Laser cladding, an innovative surface modification and coating preparation process, has emerged as a research hotspot in material surface modification and green remanufacturing domains. In the laser cladding process, the interaction between laser light, powder particles, and the substrate results in a complicated mapping connection between process parameters and clad layer quality. This work aims to shed light on this mapping using fast evolving machine learning algorithms. A full factorial experimental design was employed to clad Inconel 718 powder on an A286 substrate comprising 64 groups. Analysis of variance, contour plots, and surface plots were used to explore the effects of laser power, powder feeding rate, and scanning speed on the width, height, and dilution rate of the cladding. The performance of the predictive models was evaluated using the index of merit (IM), which includes mean square error (MSE), mean absolute error (MAE), and coefficient of determination (R2). By comparing the performance of the models, it was found that the Extra Trees, Random forest regression, Decision tree regression, and XGBoost algorithms exhibited the highest predictive accuracy. Specifically, the Extra Trees algorithm outperformed other machine learning models in predicting the cladding width, while the RFR algorithm excelled in predicting the associated height. The DTR algorithm demonstrated the best performance in predicting the cladding dilution rate. The R2 values for width, height, and dilution rate were found to be 0.949, 0.954, and 0.912, respectively, for these three models.
Mixture ratio optimization of basalt fiber recycled aggregate concrete based on RSM
Authors: Li Xiang , Sun Xiaomeng 
Published: April 2024

Abstract
In this paper, the effects of W/B ratio, recycled aggregate (RA) content and basalt fiber (BF) dosage on the compressive strength, splitting tensile strength and slump of concrete were investigated and a regression model was developed for analysis and prediction, and the regression model was validated using ANOVA and confidence analysis. Statistical analysis revealed that W/B ratio, RA content and BF dosage had significant effects on all properties of concrete. The established regression model fits the experimental data well and can accurately predict the properties of concrete. It was also found that there was a significant interaction between W/B ratio and BF dosage, as well as RA content and BF dosage, which suggests that the combination of these factors should be considered in the design of concrete mixture ratio to achieve optimum performance. The predicted values of compressive strength, split tensile strength and slump of concrete under optimum proportioning were in good agreement with the experimental values. Therefore, optimizing the concrete proportion by response surface methodology can improve the testing efficiency and obtain basalt fiber recycled aggregate concrete that meets the design requirements and has better overall performance.
Impact of digital economy on urban land green use efficiency: evidence from Chinese cities
Authors: Wen Rou , Li Hongyi 
Published: April 2024

Abstract
Improving urban land green use efficiency (ULGUE) is essential for achieving the sustainable use of land resources and the high-quality economic development of cities. The digital economy has overcome spatial and locational constraints, blurred the boundaries between industries, and created a collaborative and open economic model, inevitably affecting urban land utilization. However, whether the digital economy will affect ULGUE and how such an effect would take place are still unclear. This study evaluates the digital economy and ULGUE of Chinese cities from 2011 to 2019 and systematically analyzes both the direct and indirect impact mechanisms through which the digital economy affects ULGUE. The results show that the digital economy can significantly enhance ULGUE, and these results prove to be reliable, as shown by various endogeneity treatments and robustness tests. The digital economy enhances ULGUE by optimizing the industrial structure (structural effect), increasing green technology innovation (technical effect), and agglomerating digital talent (scale effect). Moreover, land finance dependency plays an adverse moderating role in the relationship between the digital economy and ULGUE. Further heterogeneity analysis shows that the promoting effect of the digital economy on ULGUE takes full effect in the eastern cities, larger cities, and cities with high levels of digital economy development and land marketization. This paper presents recommendations for supporting the balanced and integrated development of the digital economy across regions and provides differentiated development strategies to enhance ULGUE in the context of digitization.
Machine learned environment-dependent corrections for a
spds∗
empirical tight-binding basis
Authors: Soccodato Daniele , Penazzi Gabriele , Pecchia Alessandro , Phan Anh-Luan , Auf der Maur Matthias 
Published: April 2024

Abstract
Empirical tight-binding (ETB) methods have become a common choice to simulate electronic and transport properties for systems composed of thousands of atoms. However, their performance is profoundly dependent on the way the empirical parameters were fitted, and the found parametrizations often exhibit poor transferability. In order to mitigate some of the the criticalities of this method, we introduce a novel Δ-learning scheme, called MLΔTB. After being trained on a custom data set composed of ab-initio band structures, the framework is able to correlate the local atomistic environment to a correction on the on-site ETB parameters, for each atom in the system. The converged algorithm is applied to simulate the electronic properties of random GaAsSb alloys, and displays remarkable agreement both with experimental and ab-initio test data. Some noteworthy characteristics of MLΔTB include the ability to be trained on few instances, to be applied on 3D supercells of arbitrary size, to be rotationally invariant, and to predict physical properties that are not exhibited by the training set.
The role of the basic state in the climate response to future Arctic sea ice loss
Authors: Sigmond M , Sun L 
Published: April 2024

Abstract
There is great uncertainty in the atmospheric circulation response to future Arctic sea ice loss, with some models predicting a shift towards the negative phase of the North Atlantic Oscillation (NAO), while others predicting a more neutral NAO response. We investigate the potential role of systematic model biases in the spread of these responses by modifying the unperturbed (or ‘control’) climate (hereafter referred to as the ‘basic state’) of the Canadian Earth system model version 5 (CanESM5) in sea ice loss experiments based on the protocol of the Polar Amplification Model Intercomparison Project. We show that the presence or absence of the stratospheric pathway in response to sea ice loss depends on the basic state, and that only the CanESM5 version that shows a weakening of the stratospheric polar vortex features a strong negative NAO response. We propose a mechanism that explains this dependency, with a key role played by the vertical structure of the winds in the region between the subtropical jet and the stratospheric polar vortex (‘the neck region winds’), which determines the extent to which anomalous planetary wave activity in response to sea ice loss propagates away from the polar vortex. Our results suggest that differences in the models’ basic states could significantly contribute to model spread in the simulated atmospheric circulation response to sea ice loss, which may inform efforts to narrow the uncertainties regarding the impact of diminishing sea ice on mid-latitude climate.
Headlining mental health in a changing climate: a systematic analysis of climate change and mental health news coverage from Canada and the United States
Authors: Aylward Breanne , Cunsolo Ashlee , Vriezen Rachael , Bayne Hannah L , King Nia , Harper Sherilee 
Published: April 2024

Abstract
Climate change exerts a profound and far-reaching toll on mental health, resulting in mental illness, diminished wellbeing, and strained social relations, with the severity of these impacts anticipated to intensify under future climate change. News coverage of climate-mental health issues can shape public perceptions and responses, and therefore understanding this coverage is vital for creating and implementing strategies to lessen climate-mental health risks. We systematically examined the extent, nature, and range of news articles from Canada and the United States that covered climate-mental health impacts. Five electronic databases were searched. Articles were included if they were print or online news stories that covered climate-mental health impacts and were published in English or French by sources in Canada or the United States between 2016 and 2020. A total of 1085 articles (642 unique stories) met the inclusion criteria and underwent data extraction and analysis using descriptive statistics and thematic analysis. Coverage of climate-mental health outcomes increased in both Canada and the United States from 2016 to 2019. There was, however, a substantial decrease in coverage by Canadian news outlets from 2019 to 2020. Further, although 468 different news outlets published at least one story on the topic, repeat coverage by any one news outlet was infrequent. Most opinion pieces presented climate-mental health impacts as legitimate or expressed support for people experiencing these issues. Roughly half of the included stories identified populations that are vulnerable to climate-mental health impacts, particularly children and young people. Additionally, approximately half of the included stories identified potential interventions or coping strategies to protect mental health, most often involving changes to individual lifestyles or behavior. More sustained coverage that focuses on protective factors, interventions, and coping strategies is needed, as this could help foster public understanding and drive action to reduce climate-mental health risks.
A systematic review of urban green and blue spaces and cognitive function including discussion of mechanistic pathways
Authors: Glover Sophie , Cleland Claire L , Trott Mike , Hunter Ruth F 
Published: April 2024

Abstract
Urban green and blue spaces (UGBSs) have been found to have health-enhancing properties (e.g. promotion of physical activity, improved social connectedness, and stress reduction). We examined the associations between UGBSs and cognitive function and aimed to identify any mechanistic pathways involving UGBSs and cognitive function. The initial search of four databases (MEDLINE, Embase, PSYCHInfo, and Web of Science) yielded 4838 studies when duplicates were removed to undergo abstract screening. Following abstract and full text screening, the included studies were classified as ‘observational’ (proximity to UGBSs, n = 28/35) or ‘interventional’ (n = 7/35). Of the included studies, 71.4% (n = 24/28) of ‘observational’ studies and 57.1% (n = 4/7) of ‘interventional’ studies found positive associations indicating that UGBSs are beneficial for cognitive function (i.e. enhance cognitive function, lower risk of cognitive impairment, or protect cognitive function). Overall, 71.4% (n = 20/35) of studies included within this review were considered to have a medium risk of bias. Current studies have identified relationships between UGBSs and cognitive function; however, further work is required globally to broaden our understanding and provide a reliable evidence base. Current literature has elucidated numerous mechanistic pathways by which UGBSs have the capacity to operate, including attention restoration theory and stress reduction theory. Advancing the evidence for the mechanistic pathways between UGBSs and cognitive function is required. This may advise future UGBS policies to improve the health and well-being of both the environment and the globally ageing population.
Depoliticization and State Authority
Authors: Schupmann Benjamin A 
Published: April 2024

Abstract
This chapter analyses the legitimacy of the state’s defence of its constitutional identity against internal challenges such as politicization, enemies, and legal revolution, using Carl Schmitt’s state and constitutional theory. Building on Thomas Hobbes’ state theory, Schmitt argues that the state possesses the right to defend its political identity through methods of constitutional entrenchment. Although formulated before the term ‘militant democracy’ emerged, Schmitt’s theory anticipated its principal mechanisms, including the unamendability of constitutional essentials and political rights restrictions. The chapter concludes by highlighting that while Schmitt’s thought provides the militant dimension of a liberal normative theory of militant democracy, it fails to provide any significant democratic aspects. Therefore, to fully realize a liberal normative theory of militant democracy, Schmitt’s formal arguments must be supplemented with substantive democracy theory.
Conclusion
Authors: Schupmann Benjamin A 
Published: April 2024

Abstract
The conclusion of this book underscores how ‘militant democracy’ is vital for entrenching democratic constitutional essentials against legal revolutionary threats. It argues for the use of proactive defensive measures to safeguard the political identity of democracy against its internal enemies. While emphasizing the importance of constitutional design in safeguarding democracy, the conclusion recognizes that militant democracy should be integrated into a broader defensive strategy. It argues that militant democracy’s focus on constitutional entrenchment should be paired with more proactive and longer-term solutions, such as improved social democracy and civic education. It concludes that a multifaceted defence is the best guarantee against the cannibalization of democracy.
Rapid examination of lung tissues by nonlinear microscopy
Authors: Sun Yue , Weber Timothy D , Fujimoto James G , Rosen Seymour , VanderLaan Paul A 
Published: April 2024

Abstract

Objectives
Traditional histopathology is a time-intensive and labor-intensive process involving tissue formalin fixation, paraffin embedding, and microtoming into thin sections for H&E staining. Frozen section analysis is a modality used during surgery to quickly evaluate tissue, but it has limitations, such as the size and number of the specimens that can be analyzed as well as difficulties with fatty and bony tissues. Our objective was to investigate the performance of nonlinear microscopy, a fluorescence microscopy technique, for the rapid examination of resected lung tumors.

Methods
In this proof-of-principle study, nonlinear microscopy imaging of resected lung tissue was performed on a total of 73 tissue specimens collected from 13 patients who underwent lobectomy, segmentectomy, or wedge resection for pulmonary nodules.

Results
Two pathologists reviewed the digital nonlinear microscopy images in comparison to the corresponding histopathologic H&E slides from a variety of pulmonary pathologies.

Conclusions
This study demonstrated that nonlinear microscopy readily replicates traditional H&E staining for both lung tumors and nonneoplastic pulmonary structures. Nonlinear microscopy provides many advantages over frozen section analysis and is an optical imaging platform that has the potential to augment rapid pathologic evaluation of resected tissues in the age of digital pathology.
How I diagnose systemic mastocytosis
Authors: Rets Anton V , George Tracy I 
Published: April 2024

Abstract

Objectives
Systemic mastocytosis (SM) is a neoplasm of mast cells (MCs) characterized by their proliferation in extracutaneous organs. Systemic mastocytosis includes several entities with different clinical courses and prognoses. The rarity of this disease and the diversity of clinical and morphologic presentation make the diagnosis of SM very challenging. The aim of this review is to share our approach to the diagnosis of SM.

Methods
We present 4 cases that highlight the spectrum of clinical and laboratory features of SM and outline the diagnostic process with an emphasis on morphology.

Results
Pathology and laboratory medicine play a key role in investigation of SM, as correct diagnosis requires integration of morphologic, molecular, and serologic findings. In addition to awareness of microscopic findings in SM, a pathologist must keep abreast with an expanding menu of ancillary studies, particularly molecular testing.

Conclusions
Systemic mastocytosis is a challenging diagnosis that requires not only a demonstration of a clonal proliferation of MCs but also a correct subclassification based on the recently updated criteria.
Bringing home the benefits: do pro-family employee benefits mitigate the risk of depression from competing workplace and domestic labor roles?
Authors: Platt Jonathan M , Bates Lisa , Jager Justin , McLaughlin Katie A , Keyes Katherine M 
Published: April 2024

Abstract
Despite significant historical progress toward sex/gender parity in employment status in the United States, women remain more likely to provide domestic labor, creating role competition which may increase depression symptoms. Pro-family employee benefits may minimize the stress of competing roles. We tested whether depressive symptoms were higher among women with competing roles versus without competing roles and whether this effect was greater among women without (vs with) pro-family benefits. Data included employed women (n = 9884 person-years) surveyed across 4 waves (2010, 2015, 2017, and 2019) of the National Longitudinal Survey 1997. Depression symptoms were measured with the 5-item short version of the Mental Health Inventory (MHI-5). The effect of interaction between competing roles and pro-family employee benefits on depressive symptoms was also compared with that of non–family-related benefits, using marginal structural models to estimate longitudinal effects in the presence of time-varying confounding. MHI-5 scores were 0.56 points higher (95% CI, 0.15-0.97) among women in competing roles (vs not). Among women without pro-family benefits, competing roles increased MHI-5 scores by 6.10 points (95% CI, 1.14-11.1). In contrast, there was no association between competing roles and MHI-5 scores among women with access to these benefits (MHI-5 difference = 0.44; 95% CI, −0.2 to 1.0). Results were similar for non–family-related benefits. Dual workplace and domestic labor role competition increases women’s depression symptoms, though broad availability of workplace benefits may attenuate that risk.
This article is part of a Special Collection on Mental Health.
Unraveling the molecular mechanism of the interaction between cyclodextrin-based nanoparticles (CDNPs) and paroxetine hydrochloride
Authors: Doan Anh Thi Ngoc , Sakurai Kazuo 
Published: April 2024

Abstract
Cyclodextrin-based nanoparticles (CDNPs) have shown promise as versatile carriers for improving drug delivery systems. This study investigates the binding constants governing the interaction between paroxetine hydrochloride (PRX) and β-cyclodextrin (βCD) and β-cyclodextrin epichlorohydrin polymer (βCDNP), utilizing a range of methodologies. The findings demonstrate enhanced binding affinity between PRX and βCDNP, offering insights into the binding behavior. Furthermore, the presence of a 2:1 βCD-PRX inclusion complex within the polymer suggests potential applications in drug delivery, particularly for improving solubility and stability of poorly water-soluble drugs. These results contribute to our understanding of host-guest interactions, with implications for enhancing therapeutic efficacy and patient outcomes. The study offers valuable insights into supramolecular chemistry and pharmaceutical sciences, paving the way for more effective drug delivery systems.
Integration of graph network with kernel SVM and logistic regression for identification of biomarkers in SCA12 and its diagnosis
Authors: Agrawal Snigdha , Agrawal Ramesh Kumar , Kumaran S Senthil , Rana Bharti , Srivastava Achal Kumar 
Published: April 2024

AbstractSpinocerebellar ataxia type 12 is a hereditary and neurodegenerative illness commonly found in India. However, there is no established noninvasive automatic diagnostic system for its diagnosis and identification of imaging biomarkers. This work proposes a novel four-phase machine learning–based diagnostic framework to find spinocerebellar ataxia type 12 disease–specific atrophic-brain regions and distinguish spinocerebellar ataxia type 12 from healthy using a real structural magnetic resonance imaging dataset. Firstly, each brain region is represented in terms of statistics of coefficients obtained using 3D-discrete wavelet transform. Secondly, a set of relevant regions are selected using a graph network–based method. Thirdly, a kernel support vector machine is used to capture nonlinear relationships among the voxels of a brain region. Finally, the linear relationship among the brain regions is captured to build a decision model to distinguish spinocerebellar ataxia type 12 from healthy by using the regularized logistic regression method. A classification accuracy of 95% and a harmonic mean of precision and recall, i.e. F1-score of 94.92%, is achieved. The proposed framework provides relevant regions responsible for the atrophy. The importance of each region is captured using Shapley Additive exPlanations values. We also performed a statistical analysis to find volumetric changes in spinocerebellar ataxia type 12 group compared to healthy. The promising result of the proposed framework shows that clinicians can use it for early and timely diagnosis of spinocerebellar ataxia type 12.