bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incidence and risk factors of prostate cancer among the Northern and Eastern parts of the United Arab Emirates population
Authors: Al Shareef Zainab , Al‐Shahrabi Rula , Saheb Sharif‐Askari Fatemeh , AlDhmanie Amna , Alshamsi Younis , Zarooni Abdulqadir Al , Mahmoud Rabah Al , Soliman Sameh S. M. , Halwani Rabih , Bendardaf Riyad 
Published: November 2023

AbstractBackgroundProstate cancer (PCa) is a prevalent disease worldwide. However, the incidence and patient‐specific risk factors of PCa in the Middle East, specifically in the United Arab Emirates, have not been previously reported.MethodsWe conducted a retrospective cohort study on 2377 men diagnosed with either benign prostatic hyperplasia (BPH) or PCa in the Northern and Eastern regions of the United Arab Emirates, excluding the Western part, which includes Abu Dhabi. The study spanned from January 2012 and December 2021. To calculate the PCa incidence rate, we utilized the world age‐standardized incidence rates (W‐ASIR) categorized by age groups. Patient‐specific risk factors of PCa were identified through a multivariate logistic regression analysis of clinical data.ResultsA total of 247 cases of PCa and 2130 cases of BPH were included in the study. In our cohort, the W‐ASIR for PCa was 21.3 per 100,000 men. The incidence of PCa showed an increasing trend with age, with the highest incidence observed among men aged 70 years and older. Accordingly, multivariate analysis revealed that age over 70 was associated with an increased risk of PCa (OR: 2.546, 95% confidence interval [CI]: 1.892−3.425, p < 0.01). On the other hand, preexisting conditions such as hypertension and diabetes mellitus were found to lower the risk of PCa (OR: 0.222, 95% CI: 0.163−0.302, p < 0.001) and (OR: 0.364, 95% CI: 0.205−0.648, p < 0.001), respectively. Additionally, metformin intake was associated with a reduced risk of PCa (OR: 0.385, 95% CI: 0.190−0.782, p = 0.008); while insulin usage increased the risk of PCa (OR: 2.586, 95% CI: 1.539−4.344, p < 0.001). Anti‐BPH medications such as phosphodiesterase inhibitors (OR: 0.223, 95% CI: 0.069−0.723, p = 0.012) or 5‐α reductase (OR: 0.206, 95% CI: 0.110−0.389, p < 0.000), were found to lower the risk of PCa.ConclusionThe findings underscore the high incidence of PCa in the United Arab Emirates, with age being a significant factor. Furthermore, the study highlights the influence of certain comorbidities and medications on the risk of developing PCa within the United Arab Emirates population.
Development of PE‐based antibacterial and antioxidant films with L‐ascorbic acid‐p‐hydroxybenzoate addition
Authors: Tang Yali , Zhu Junhui , Li Yan , Lu Lixin , Qiu Xiaolin , Pan Liao 
Published: November 2023

AbstractIn this work, a PE‐based antibacterial and antioxidant material was successfully developed. L‐Ascorbic acid and p‐hydroxybenzoic acid were used as raw materials to synthesize L‐ascorbic acid‐p‐hydroxybenzoate (LPHB) by direct esterification method. LPHB was added to polyvinyl alcohol (PVA) solution and coated on corona‐treated low‐density polyethylene (LDPE) film coated with primer layer to prepare a composite film. The effects of different concentrations of LPHB on the performance of composite films were investigated to determine the optimal amount of addition, and then to prepare both antibacterial and antioxidant films. The antimicrobial properties of LPHB were analysed. The antibacterial, antioxidant, mechanical, barrier properties and morphology of the films were characterized and analysed. The results showed that the addition of LPHB significantly improved the antibacterial and anti‐mould properties, oxidation resistance, and barrier properties of the composite film compared to the LDPE film. The best overall performance of the composite film was achieved when the content of LPHB was 1.5%, the antibacterial rate against Escherichia coli and Staphylococcus aureus reached 99%, and the free radical scavenging rate reached 67.22%. In addition, the cling film added with LPHB has better antioxidant and antibacterial properties, which has obvious effect on bread preservation and has potential for application in food packaging.
Tracking sustainable development from the dual perspective of environmental and economic performance: A dynamic framework and coupling coordination degree
Authors: Gu Jiaxing , Zeng Shouzhen , Chen Wendi , Balezentis Tomas , Sapolaite Vaida 
Published: November 2023

AbstractEvaluation of green development is crucial for policy analysis and decision‐making. To address the research gap on green development assessment systems, this study first presents the Super‐efficiency Bounded Adjusted Measure model to gage the green growth index and economic growth index. This analysis involves evaluation of the coupling coordination degree. Through the analysis of the coordination between green growth and economic growth leads to recommendations for each region under consideration in regards to promotion of the components of the sustainable growth. This study presents the model that melds the objectives of the green and economic growth and uses the results for constructing the sustainable development Lorenz curve and Gini coefficient for the analysis of the differences in the sustainable development levels across the regions. The empirical case is presented to show the possibilities for application of the proposed approach.
2D and 3D Micropatterning of Mussel‐Inspired Functional Materials by Direct Laser Writing
Authors: Tavasolyzadeh Zeynab , Tang Peng , Hahn Marc Benjamin , Hweidi Gada , Nordholt Niclas , Haag Rainer , Sturm Heinz , Topolniak Ievgeniia 
Published: November 2023

AbstractThis work addresses the critical need for multifunctional materials and substrate‐independent high‐precision surface modification techniques that are essential for advancing microdevices and sensing elements. To overcome existing limitations, the versatility of mussel‐inspired materials (MIMs) is combined with state‐of‐the‐art multiphoton direct laser writing (DLW) microfabrication. In this way, 2D and 3D MIM microstructures of complex designs are demonstrated with sub‐micron to micron resolution and extensive post‐functionalization capabilities. This study includes polydopamine (PDA), mussel‐inspired linear, and dendritic polyglycerols (MI‐lPG and MI‐dPG), allowing their direct microstructure on the substrate of choice with the option to tailor the patterned topography and morphology in a controllable manner. The functionality potential of MIMs is demonstrated by successfully immobilizing and detecting single‐stranded DNA on MIM micropattern and nanoarray surfaces. In addition, easy modification of MIM microstructure with silver nanoparticles without the need of any reducing agent is shown. The methodology developed here enables the integration of MIMs in advanced applications where precise surface functionalization is essential.
Universal boosting ML approaches to predict the ultimate load capacity of CFST columns
Authors: Nguyen Thuy‐Anh , Le Nguyen Khuong , Ly Hai‐Bang 
Published: November 2023

SummaryEstablishing a universal machine learning (ML) model in structural engineering is vital for understanding how various parameters, like geometry and material properties, influence a structure's behavior. This study aims to create a comprehensive ML model that considers the impact of different cross‐sectional parameters on the ultimate load capacity (ULC) of concrete‐filled steel tube (CFST) columns. This model assists engineers in making informed design decisions. The study employs a large dataset of 3094 data points with diverse geometric and material properties of CFST columns. After adjusting input features, robust boosting ML models (Catboost, LightGBM, and XGB) are meticulously fine‐tuned using grid search and fivefold cross‐validation. Monte Carlo simulation is used for further assessment. The results demonstrate that the most accurate XGB model delivers impressive accuracy, comparable to or better than existing literature models that focused on a single CFST column cross‐section. The chosen XGB model is then utilized for feature importance analysis, local performance assessment, and sensitivity analysis through 1‐D and 2‐D partial dependence plots. These analyses help assess the input's contribution and effect on ULC prediction for CFST columns.
Toward a justice‐centered ambitious teaching framework: Shaping ambitious science teaching to be culturally sustaining and productive in a rural context
Authors: Luehmann April , Zhang Yang , Boyle Heather , Tulbert Eve , Merliss Gena , Sullivan Kyle 
Published: November 2023

AbstractWe find ourselves at a time when the need for transformation in science education is aligning with opportunity. Significant science education resources, namely the Next Generation Science Standards (NGSS) and the Ambitious Science Teaching (AST) framework, need an intentional aim of centering social justice for minoritized communities and youth as well as practices to enact it. While NGSS and AST provide concrete guidelines to support deep learning, revisions are needed to explicitly promote social justice. In this study, we sought to understand how a commitment to social justice, operationalized through culturally sustaining pedagogy (Paris, Culturally sustaining pedagogies and our futures. The Educational Forum, 2021; 85, pp. 364–376), might shape the AST framework to promote more critical versions of teaching science for equity. Through a qualitative multi‐case study, we observed three preservice teacher teams engaged in planning, teaching, and debriefing a 6‐day summer camp in a rural community. Findings showed that teachers shaped the AST sets of practices in ways that sustained local culture and addressed equity aims: anchoring scientific study in phenomena important to community stakeholders; using legitimizing students' stories by both using them to plan the following lessons and as data for scientific argumentation; introducing local community members as scientific experts, ultimately supporting a new sense of pride and advocacy for their community; and supporting students in publicly communicating their developing scientific expertise to community stakeholders. In shaping the AST framework through culturally sustaining pedagogy, teachers made notable investments: developing local networks; learning about local geography, history, and culture; building relationships with students; adapting lessons to incorporate students' ideas; connecting with community stakeholders to build scientific collaborations; and preparing to share their work publicly with the community. Using these findings, we offer a justice‐centered ambitious science teaching (JuST) framework that can deliver the benefits of a framework of practices while also engaging in the necessarily more critical elements of equity work.
The use of gene expression datasets in feature selection research: 20 years of inherent bias?
Authors: Grisci Bruno I. , Feltes Bruno César , de Faria Poloni Joice , Narloch Pedro H. , Dorn Márcio 
Published: November 2023

AbstractFeature selection algorithms are frequently employed in preprocessing machine learning pipelines applied to biological data to identify relevant features. The use of feature selection in gene expression studies began at the end of the 1990s with the analysis of human cancer microarray datasets. Since then, gene expression technology has been perfected, the Human Genome Project has been completed, new microarray platforms have been created and discontinued, and RNA‐seq has gradually replaced microarrays. However, most feature selection methods in the last two decades were designed, evaluated, and validated on the same datasets from the microarray technology's infancy. In this review of over 1200 publications regarding feature selection and gene expression, published between 2010 and 2020, we found that 57% of the publications used at least one outdated dataset, 23% used only outdated data, and 32% did not cite data sources. Other issues include referencing databases that are no longer available, the slow adoption of RNA‐seq datasets, and bias toward human cancer data, even for methods designed for a broader scope. In the most popular datasets, some being 23 years old, mislabeled samples, experimental biases, distribution shifts, and the absence of classification challenges are common. These problems are more predominant in publications with computer science backgrounds compared to publications from biology and can lead to inaccurate and misleading biological results.This article is categorized under:
Algorithmic Development > Biological Data Mining
Technologies > Machine Learning
Introduction: Has Cycling Got a Boost from the Pandemic?
Authors: Ortar Nathalie , Rérat Patrick 
Published: November 2023

AbstractAs the COVID-19 pandemic surged around the world at the beginning of 2020, all aspects of life were disrupted. This book looks back to spring 2020 and the end of the first lockdown, when many cities around the globe took measures to give cycling more space. It scrutinises the political and material responses to increase cycling during the pandemic. The introduction presents the 9 chapters as well as some of the lessons learned.
Public Action in Times of Crisis: Trajectories of Cycling Policies in Four French Cities
Authors: Thébert Mariane , Eskenazi Manon , Adam Matthieu , Baudelle Guy , Chapelon Laurent , Lammoglia Adrien , Lejoux Patricia , Marrec Sébastien , Poisson Adrien , Zimmermann Michaël 
Published: November 2023

AbstractFrench local authorities developed over 500 km of pop-up cycling infrastructure to face the Covid-19 pandemic. These experiments raise questions about the impact of a crisis situation on public decision-making and policies. This chapter reports on a comprehensive analysis of the roll-out of the Covid cycle lanes in four metropolises—Paris, Lyon, Montpellier, and Rennes—with a particular attention to the factors of continuity or interruption pre-and post-crisis. It retraces the involvement in collective action of the different actors during the crisis peak, the reactions sparked by these measures, and the status of the temporary infrastructure in the local mobility policy landscape a year after it was introduced. It shows that the crisis has served more as an accelerator than as a course changer for public policies introducing elements of change for the future by slightly modifying the actors’ interests, representations, and instruments.
Pop-Up Bike Lanes and Temporary Shared Spaces in Vienna During the COVID-19 Pandemic
Authors: Frey Harald , Laa Barbara , Leth Ulrich 
Published: November 2023

AbstractSimilar to many cities, Vienna (Austria) implemented measures to provide more space for pedestrians and cyclists during the first wave of the COVID-19 pandemic. In this chapter, the implementation process of the temporary shared spaces and “pop-up” bike lanes is described, and the evaluation results regarding their usage as well as the political decisions of their early removal are presented. With video recordings and manual counting, we found that pop-up bike lanes were well adopted by cyclists, but temporary shared spaces have largely failed to attract pedestrians. The possible reasons are discussed as well as the criteria for better implementation of temporary walking and cycling infrastructure in the future. Drawing on the multiple streams theory, we link the decision of suspending all temporary infrastructures to the political situation at the time with pop-up bike lanes as a highly controversial issue before the local elections in October 2020 and a change of government afterward. We conclude that this presents a lost opportunity to permanently redistribute road space for active mobility, but future initiatives could learn from the Vienna case by thinking more strategically about political aspects.
The Spatial Dimension of “Pop-Up Cycle Paths” in Metropolitan Areas a Comparative Study of France and Colombia
Authors: Demoraes Florent , Ovtracht Nicolas , Tabaka Kamila , Duché Sarah , Mericskay Boris , Sieper Camille 
Published: November 2023

AbstractThis chapter goes over how Covid-19 pandemic impacted in space and time on cycling infrastructure in four French cities (Grenoble, Lyon, Montpellier, and Rennes) which we have compared with Bogotá (Colombia). It shows that local authorities implemented different strategies to develop their networks during this unusual period running from 2020 to 2021. The sizeable task of researching, refining, harmonising, and comparing several sources was formalised to ensure reproducibility, and a typology drawn up to compare the five cities. Certain local authorities installed equipment mainly in central spaces, while others also extended infrastructure to the outskirts, in certain cases duplicating pre-existing cycling facilities. In some cities, such as Montpellier, Grenoble, and even more markedly Bogotá, low-income districts also benefited to a certain extent from pop-up cycling infrastructure. Concerning the extent of coverage, two years after the beginning of the pandemic, most of the pop-up cycling infrastructure in the cities under study had been dismantled, or else retained on the already dense parts of the network. In several cases pop-up tracks were used to make up for missing links in the pre-existing network. They also sometimes provided a way of improving certain connections, but given the small number of pop-up paths which became lasting facilities, they have not fundamentally expanded the scale of the networks as the pandemic recedes, nor have they made the cities significantly more cycle-friendly overall.
Hunting ewinos and a light scalar of Z3-NMSSM with a bino-like dark matter in top squark decays at the LHC
Authors: Datta AseshKrishna , Guchait Monoranjan , Roy Arnab , Roy Subhojit 
Published: November 2023

Abstract
We explore a possible signal of the presence of relatively light electroweakinos (ewinos) and a singlet-like scalar (aS) of the Z3-symmetric Next-to-Minimal Supersymmetric Standard Model (Z3-NMSSM) in the cascade decays of not so heavy top squarks ($$ {m}_{{\tilde{t}}_1} $$

m

t
~

1

≲ 1.5 TeV) that may be produced in pairs at the Large Hadron Collider LHC. We work in a scenario where the lightest (next-to-lightest) SUSY particle is bino (singlino)-like with its mass below 100 GeV and is mildly tempered with higgsino and singlino admixtures. The singlet-like scalar provides an annihilation funnel for the bino-like states such that the latter could act as a viable dark matter candidate, unlike what is now highly constrained in the MSSM. We consider a pair of immediately heavier neutralinos and the lighter chargino which all are higgsino-like with masses in the range ~ 0.5–1 TeV and are still compatible with all experimental constraints. While these states may not be accessible in their direct searches at the LHC in our present scenario, such ewinos could still be traced in the decays of the top squarks of the above-mentioned kind. We consider the signal final state "Image missing" at the LHC. We find that while a usual cut-based analysis (CBA) of LHC data worth 300 fb−1 would be unable to discover such excitations, a multivariate analysis (MVA) can be reasonably sensitive to higgsino-like ewinos having masses ≳ 650 GeV when $$ {m}_{{\tilde{t}}_1} $$

m

t
~

1

≳ 1 TeV. On the other hand, with 3000 fb−1 of data, these masses become accessible in a CBA while even an MVA on such a data set is unlikely to find these ewinos with masses around 1 TeV when $$ {m}_{{\tilde{t}}_1} $$

m

t
~

1

hits ∼ 1.5 TeV.
Impact of different metal artifact reduction techniques in photon-counting computed tomography head and neck scans in patients with dental hardware
Authors: Pallasch Fabian Bernhard , Rau Alexander , Reisert Marco , Rau Stephan , Diallo Thierno , Stein Thomas , Faby Sebastian , Bamberg Fabian , Weiss Jakob 
Published: November 2023

Abstract
Objectives
Metal artifacts remain a challenge in computed tomography. We investigated the potential of photon-counting computed tomography (PCD-CT) for metal artifact reduction using an iterative metal artifact reduction (iMAR) algorithm alone and in combination with high keV monoenergetic images (140 keV) in patients with dental hardware.

Material and methods
Consecutive patients with dental implants were prospectively included in this study and received PCD-CT imaging of the craniofacial area. Four series were reconstructed (standard [PCD-CTstd], monoenergetic at 140 keV [PCD-CT140keV], iMAR corrected [PCD-CTiMAR], combination of iMAR and 140 keV monoenergetic [PCD-CTiMAR+140keV]). All reconstructions were assessed qualitatively by four radiologists (independent and blinded reading on a 5-point Likert scale [5 = excellent; no artifact]) regarding overall image quality, artifact severity, and delineation of adjacent and distant anatomy. To assess signal homogeneity and evaluate the magnitude of artifact reduction, we performed quantitative measures of coefficient of variation (CV) and a region of interest (ROI)–based relative change in artifact reduction [PCD-CT/PCD-CTstd].

Results
We enrolled 48 patients (mean age 66.5 ± 11.2 years, 50% (n = 24) males; mean BMI 25.2 ± 4.7 kg/m2; mean CTDIvol 6.2 ± 6 mGy). We found improved overall image quality, reduced artifacts and superior delineation of both adjacent and distant anatomy for the iMAR vs. non-iMAR reconstructions (all p < 0.001). No significant effect of the different artifact reduction approaches on CV was observed (p = 0.42). The ROI-based analysis indicated the most effective artifact reduction for the iMAR reconstructions, which was significantly higher compared to PCD-CT140keV (p < 0.001).

Conclusion
PCD-CT offers highly effective approaches for metal artifact reduction with the potential to overcome current diagnostic challenges in patients with dental implants.

Clinical relevance statement
Metallic artifacts pose a significant challenge in CT imaging, potentially leading to missed findings. Our study shows that PCD-CT with iMAR post-processing reduces artifacts, improves image quality, and can possibly reveal pathologies previously obscured by artifacts, without additional dose application.

Key Points
• Photon-counting detector CT (PCD-CT) offers highly effective approaches for metal artifact reduction in patients with dental fillings/implants.
• Iterative metal artifact reduction (iMAR) is superior to high keV monoenergetic reconstructions at 140 keV for artifact reduction and provides higher image quality.
• Signal homogeneity of the reconstructed images is not affected by the different artifact reduction techniques.
Effect of pH on water durability of cellulose nanofiber-reinforced starch film
Authors: Haji Abdul Hamid Izzah Durrati , Soni Raghav , Hsu Yu-I. , Uyama Hiroshi 
Published: November 2023

AbstractThe continuous use of single-use petrochemical-based plastics has created a global crisis with a significant buildup of plastic pollution. The use of biomass resources as a replacement source of plastic constituents, namely cellulose and starch, may contribute to alleviating the crisis. In this study, cellulose nanofiber-reinforced starch films were produced and studied for their pH response in terms of their swelling behavior and wet tensile strength in both freshwater and seawater conditions. Mechanically fibrillated cellulose nanofibers (MCNFs) were blended with dialdehyde starch (Di-aldS) and made into MCNF/Di-aldS films. The films were found to swell more and had a lower wet tensile strength at pH of 9. The film’s strength reduced to 1.60 MPa in basic conditions, 80% less than in acidic environment. This is related to hemiacetal crosslinking, resulted from the interactions between the modified moieties of the starches and cellulose nanofibers. Such bioplastics enhance the reusability of cellulose nanofibers and have the potential to replace conventional petrochemical plastics to create a carbon–neutral circular society.
Graphical abstract