bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alleviated environmental constraints and restructured fungal microbiome facilitate aggregate formation and stabilization in coastal mudflat saline soil amended by sewage sludge
Authors: Li Yunlong , Shen Chao , Wang Yimin , Xu Lu , Zhao Yilin , Yi Siqiang , Zuo Wengang , Yao Rongjiang , Zhang Xing , Gu Chuanhui , Shan Yuhua , Bai Yanchao 
Published: February 2023

AbstractSoil aggregates are important drivers of soil productivity. However, the relative importance of soil abiotic and biotic agents in driving aggregate formation and stabilization remain largely unexplored, especially in coastal mudflat saline soils. We amended saline soil with sewage sludge at rates of 0, 30, 75, and 150 t ha−1 to investigate the effects of sewage sludge on the particle size distribution and stability of soil aggregate and the underlying mechanisms induced by soil environmental factors and fungal community. Results revealed that the sewage sludge amendment significantly (p < 0.05) increased the proportion of macroaggregates with sizes larger than 0.25 mm (R0.25) and enhanced aggregate stability. Moreover, alleviation of saline‐alkali stress and nutrient (C, N, and P) deficiency conditions were significantly (p < 0.05) observed in sewage sludge‐amended soils. Additionally, restructured fungal communities in amended soils harbored significantly (p < 0.05) distinguishable structures and core and unique microbiomes. Particularly, fungal species belonging to Moterella significantly (p < 0.05) enriched in sludge reclaimed soils. Results derived from the random forest (RF) model accompanied by linear regression analysis revealed that soil pH, soil organic carbon, and fungal structural diversity were significantly (p < 0.05) related to aggregate composition (R0.25) and stability (geometric average diameter, GMD). Furthermore, fungal consortia composed of 20 closely interconnected operational taxonomic units (OTUs) affiliated with Ascomycota, Basidiomycota, and Zygomycota explained 28.36% and 49.88% variance of R0.25 and GMD, respectively. Overall, our results revealed the effect of sewage sludge on soil aggregation improvement in coastal areas and highlighted the respective importance of soil chemical properties and fungal microbiome in predicting aggregation status.
Technical note: First implementation of a one‐stop solution of radiotherapy with full‐workflow automation based on CT‐linac combination
Authors: Yu Lei , Zhao Jun , Xia Fan , Zhang Zhiyuan , Liu Yanfang , Zhang Wei , Zhou Jingjie , Wang Jiazhou , Hu Weigang , Zhang Zhen 
Published: February 2023

AbstractBackgroundRadiotherapy initiation is a laborious and time‐consuming process that involves multiple steps and units. Workflow automation is in demand to improve the work efficiency and patient experience.PurposeThe purposes of this study are to describe the technical characteristics and clinical performance of an AI‐powered one‐stop radiotherapy workflow for initial treatment based on CT‐linac combination, and provide insight into the behavior of full‐workflow automation in radiotherapy.MethodsBased on a CT‐integrated linear accelerator and AI model implementation, the so‐called “All‐in‐One” workflow incorporates routine procedures from simulation, autosegmentation, autoplanning, image guidance, beam delivery, and in vivo quality assurance (QA) into one scheme, while the patient is on the treatment couch. Clinical outcomes of the new workflow were evaluated for 10 enrolled patients with rectal cancer.ResultsFor the enrolled patients, manual modifications of the autosegmented target volumes were necessary. The Dice similarity coefficient and 95% Hausdorff distance before and after the modifications were 0.892 ± 0.061 and 18.2 ± 13.0 mm, respectively. The autosegmented normal tissues and automatic plans were clinically acceptable without any modifications or reoptimization. The pretreatment IGRT corrections were within 2 mm in all directions, and the EPID‐based in vivo QA showed γ passing rate of above 97% (3%/3 mm/10% threshold) at all the checkpoints, better than the results of rectal patients who followed a routine workflow. The duration of the whole process was 23.2 ± 3.5 minutes for the enrolled patients, depending mostly on the time required for manual modification and plan evaluation.ConclusionThe All‐in‐One workflow enables full‐process automation of radiotherapy via seamless procedure integration. Compared to the routine workflow, the one‐stop solution shortens the time scale it takes to ready the first treatment from days to minutes, significantly improving the patient experience and the workflow efficiency, and it also shows potential to facilitate clinical application of online adaptive replanning.
CT‐based radiomics for the identification of colorectal cancer liver metastases sensitive to first‐line irinotecan‐based chemotherapy
Authors: Qi Wei , Yang Jing , Zheng Longbo , Lu Yun , Liu Ruiqing , Ju Yiheng , Niu Tianye , Wang Dongsheng 
Published: February 2023

AbstractBackgroundChemosensitivity prediction in colorectal cancer patients with liver metastases has remained a research hotspot. Radiomics can extract features from patient imaging, and deep learning or machine learning can be used to build models to predict patient outcomes prior to chemotherapy.PurposeIn this study, the radiomics features and clinical data of colorectal cancer patients with liver metastases were used to predict their sensitivity to irinotecan‐based chemotherapy.MethodsA total of 116 patients with unresectable colorectal cancer liver metastases who received first‐line irinotecan‐based chemotherapy from January 2015 to January 2020 in our institution were retrospectively collected. Overall, 116 liver metastases were randomly divided into training (n = 81) and validation (n = 35) cohorts in a 7:3 ratio. The effect of chemotherapy was determined based on Response Evaluation Criteria in Solid Tumors. The lesions were divided into response and nonresponse groups. Regions of interest (ROIs) were manually segmented, and sample sizes of 1×1×1, 3×3×3, 5×5×5 mm3 were used to extract radiomics features. The relevant features were identified through Pearson correlation analysis and the MRMR algorithm, and the clinical data were merged into the artificial neural network. Finally, the p‐model was obtained after repeated learning and testing.ResultsThe p‐model could distinguish responders in the training (area under the curve [AUC] 0.754, 95% CI 0.650‐0.858) and validation cohorts (AUC 0.752 95% CI 0.581‐0.904). AUC values of the pure image group model are 0.720 (95% CI 0.609‐0.827) and 0.684 (95% CI 0.529‐0.890) for the training and validation cohorts respectively. As for the clinical data model, AUC values of the training and validation cohorts are 0.638 (95% CI 0.500‐0.757) and 0.545 (95% CI 0.360‐0.785), respectively. The performances of the latter two are less than that of the former.ConclusionThe p‐model has the potential to discriminate colorectal cancer patients sensitive to chemotherapy. This model holds promise as a noninvasive tool to predict the response of colorectal liver metastases to chemotherapy, allowing for personalized treatment planning.
A novel approach to infectious disease control and radiotherapy risk management
Authors: Islam Naveed M. , Wadi‐Ramahi Shada J. , Lalonde Ron , Baig Tanvir , diMayorca Maria , Clump David A. , Huq M. Saiful 
Published: February 2023

AbstractBackgroundInfectious disease outbreaks have always presented challenges to the operation of healthcare systems. In particular, the treatment of cancer patients within Radiation Oncology often cannot be delayed or compromised due to infection control measures. Therefore, there is a need for a strategic approach to simultaneously managing infection control and radiotherapy risks.PurposeTo develop a systematic risk management method that uses mathematical models to design mitigation efforts for control of an infectious disease outbreak, while ensuring safe delivery of radiotherapy.MethodsA two‐stage failure mode and effect analysis (FMEA) approach is proposed to modify radiotherapy workflow during an infectious disease outbreak. In stage 1, an Infection Control FMEA (IC‐FMEA) is conducted, where risks are evaluated based on environmental parameters, clinical interactions, and modeling of infection risk. occupancy risk index (ORI) is defined as a metric for infection transmission risk level in each room, based on the degree of occupancy. ORI, in combination with ventilation rate per person (Rp), is used to provide a broad infection risk assessment of workspaces. For detailed IC‐FMEA of clinical processes, infection control failure mode (ICFM) is defined to be any instance of disease transmission within the clinic. Infection risk priority number (IRPN) has been formulated as a function of time, distance, and degree of protective measures. Infection control measures are then systematically integrated into the workflow. Since the workflow is perturbed by infection control measures, there is a possibility of introducing new radiotherapy failure modes or increased likelihood of existing failure modes. Therefore, in stage 2, a conventional radiotherapy FMEA (RT‐FMEA) should be performed on the adjusted workflow.ResultsThe COVID‐19 pandemic was used to illustrate stage 1 IC‐FMEA. ORI and Rp values were calculated for various workspaces within a clinic. A deep inspiration breath hold (DIBH) CT simulation was used as an example to demonstrate detailed IC‐FMEA with ICFM identification and IRPN evaluation. A total of 90 ICFMs were identified in the DIBH simulation process. The calculated IRPN values were found to be progressively decreasing for workflows with minimal, moderate, and enhanced levels of protective measures.ConclusionThe framework developed in this work provides tools for radiotherapy clinics to systematically assess risk and adjust workflows during the evolving circumstances of any infectious disease outbreak.
Unpaired low‐dose computed tomography image denoising using a progressive cyclical convolutional neural network
Authors: Li Qing , Li Runrui , Li Saize , Wang Tao , Cheng Yubin , Zhang Shuming , Wu Wei , Zhao Juanjuan , Qiang Yan , Wang Long 
Published: February 2023

AbstractBackgroundReducing the radiation dose from computed tomography (CT) can significantly reduce the radiation risk to patients. However, low‐dose CT (LDCT) suffers from severe and complex noise interference that affects subsequent diagnosis and analysis. Recently, deep learning‐based methods have shown superior performance in LDCT image‐denoising tasks. However, most methods require many normal‐dose and low‐dose CT image pairs, which are difficult to obtain in clinical applications. Unsupervised methods, on the other hand, are more general.PurposeDeep learning methods based on GAN networks have been widely used for unsupervised LDCT denoising, but the additional memory requirements of the model also hinder its further clinical application. To this end, we propose a simpler multi‐stage denoising framework trained using unpaired data, the progressive cyclical convolutional neural network (PCCNN), which can remove the noise from CT images in latent space.MethodsOur proposed PCCNN introduces a noise transfer model that transfers noise from LDCT to normal‐dose CT (NDCT), denoised CT images generated from unpaired CT images, and noisy CT images. The denoising framework also contains a progressive module that effectively removes noise through multi‐stage wavelet transforms without sacrificing high‐frequency components such as edges and details.ResultsCompared with seven LDCT denoising algorithms, we perform a quantitative and qualitative evaluation of the experimental results and perform ablation experiments on each network module and loss function. On the AAPM dataset, compared with the contrasted unsupervised methods, our denoising framework has excellent denoising performance increasing the peak signal‐to‐noise ratio (PSNR) from 29.622 to 30.671, and the structural similarity index (SSIM) was increased from 0.8544 to 0.9199. The PCCNN denoising results were relatively optimal and statistically significant. In the qualitative result comparison, PCCNN without introducing additional blurring and artifacts, the resulting image has higher resolution and complete detail preservation, and the overall structural texture of the image is closer to NDCT. In visual assessments, PCCNN achieves a relatively balanced result in noise suppression, contrast retention, and lesion discrimination.ConclusionsExtensive experimental validation shows that our scheme achieves reconstruction results comparable to supervised learning methods and has performed well in image quality and medical diagnostic acceptability.
Copolymerization of ω‐Alkenyltrimethylsilane/Propylene with Heterogeneous Ziegler‐Natta Catalyst: How Dose Alkenyl Length Affect Comonomer Incorporation?
Authors: Chen Fengtao , Zhang Zhijian , Qin Yawei , Dong Jin‐Yong 
Published: February 2023

AbstractThree ω‐alkenyltrimethylsilanes of different alkenyl moieties, i.e., 3‐butenyltrimethylsilane, 5‐hexenyltrimethylsilane, and 7‐octenyltrimethylsilane, are copolymerized with propylene over a heterogeneous Ziegler‐Natta catalyst. The experimental results reveal that, at odds with what the molecular volumes will foretell, 5‐hexenyltrimethylsilane top the three ω‐alkenyltrimethylsilanes in incorporation rate into PP while 3‐butenyltrimethylsilane becomes the most sluggish of the three. This comonomer incorporation rate order is in line with that of ω‐alkenylmethyldichlorosilanes in copolymerization with propylene‐synthesizing long‐chain‐branched PP (LCB‐PP), pointing to a peculiar alkenyl length effect on comonomer incorporation rate for these comonomers. DFT simulation is then applied to seek energetic basis in coordination‐insertion for such an effect. It is revealed that complexation abilities of the three ω‐alkenyltrimethylsilanes decrease in the following order: 3‐butenyltrimethylsilane > 5‐hexenyltrimethylsilane > 7‐octenyltrimethylsilane, in line with their molecular sizes. However, the insertion energy barriers increase in the order of: 5‐hexenyltrimethylsilane < 7‐octenyltrimethylsilane < 3‐butenyltrimethylsilane. The repulsive interaction between the bulky trimethylsilane functionality of ω‐alkenyltrimethylsilanes and growing PP chain is found to contribute significantly to the insertion energy barrier, which grows disproportionally large with 3‐butenyltrimethylsilane. The current discovery will be conducive to understanding the more complex ω‐alkenylmethyldichlorosilane/propylene copolymerization that synthesizes the industrially important LCB‐PP.
Use of non‐isothermal DSC in comparative studies of tin(II) systems for the ring‐opening polymerization ofd‐lactide
Authors: Phetsuk Sawarot , Molloy Robert , Topham Paul D , Tighe Brian J , Meepowpan Puttinan , Limwanich Wanich , Punyodom Winita 
Published: February 2023

AbstractUnderstanding the kinetics and mechanisms of polymerization, particularly the role of a catalyst or initiator used, allows for the manipulation and control of the fabrication of new materials by the most convenient, straightforward routes. The kinetics of the bulk ring‐opening polymerization (ROP) ofd‐lactide, a useful monomer employed to control the properties of poly(l‐lactide), have been studied herein to identify a relatively quick (1 h), controlled, yet convenient route to moderately high molecular weight poly(d‐lactide). Tin(II) octoate (Sn(Oct)2), Sn(Oct)2/n‐butanol (nBuOH) and liquid tin(II) butoxide (Sn(OnBu)2) as initiating systems were investigated by non‐isothermal differential scanning calorimetry (DSC). Isoconversional methods were employed to determine the activation energy (Ea) for each reaction. The results showed that liquid Sn(OnBu)2was a more efficient initiator than the commonly reported initiating systems of Sn(Oct)2and Sn(Oct)2/nBuOH in terms of producing higher polymerization rates and polymer molecular weights. High‐molecular‐weight poly(d‐lactide) (1.8 × 105 Da) with moderate dispersity (Ð = 1.3) was obtained using 0.1 mol% liquid Sn(OnBu)2as the initiator at 120 °C. This work describes the applications of non‐isothermal DSC and isoconversional methods in comparing the effectiveness of different initiators in the bulk ROP ofd‐lactide for the first time. © 2023 Society of Chemical Industry.
A Static and Spherically Symmetric Hairy Black Hole in the Framework of the Gravitational Decoupling
Authors: Avalos R. , Bargueño Pedro , Contreras E. 
Published: February 2023

AbstractIn this work we construct a static and spherically symmetric black hole geometry supported by a family of generic mono‐parametric sources thorough the Gravitational Decoupling. The parameter characterizing the matter sector can be interpreted as hair which cannot be associated to any global charge. Although the solution is constructed by demanding the weak energy condition, we find that the resulting matter sector satisfies all the energy conditions at and outside the horizon. We study the effect of the hair on the periastron advance and the gravitational lensing of the black hole. We estimate the best WKB order to compute the quasinormal frequencies for scalar, vector and tensor perturbation fields.
Urban Mobility Transition Driven by New Digital Technologies
Authors: de la Cruz Teresa , Royo Beatriz , Ciprés Carolina 
Published: February 2023

AbstractThe urban mobility landscape for both, freight and passengers, is in transition. During the last decade new business models, enabled by digital technologies, are blooming. However, sometimes the new mobility solutions do not fit with local regulations, their impacts are unclear, and legislative issues are hindering the economic niche exploitation and their implementation. This chapter describes the current transition that urban mobility systems are undergoing and presents an approach for guiding cities towards the implementation and adoption of new digital urban mobility solutions. This approach, based on the Horizon 2020 SPROUT project, consists of assessing the impacts and feasibility of the new mobility solutions, identifying areas where policy intervention to enable the implementation would be required and co-creating those specific policies with all the urban mobility stakeholders. This is complemented by an implementation feasibility and user acceptance analysis.
Universal Design and Transport Innovations: A Discussion of New Mobility Solutions Through a Universal Design Lens
Authors: Aarhaug Jørgen 
Published: February 2023

AbstractMost technological advances in mobility result in better accessibility for many, yet the benefits remain unevenly distributed. Universal design is a strategy to counter social exclusion, involving the design of products and environments to be usable by all people, to the greatest extent possible, without the need for adaptation or specialised design New and improved mobility technologies typically result in increased mobility. However, most new technologies create both winners and losers – and who wins and who loses depends on how the mobility solution in question is introduced to the mobility system. This study finds that many of the new mobility technologies that are introduced, though not directly relating to universal design, strongly affect the universality of access to mobility. The chapter aims to give insight into how certain new mobility solutions affect different user groups, and to highlight how the outcome is a function of the interplay between technology and its implementation. The paper concludes by pointing at the need for regulation to align the objectives of the actors behind new technologies and an inclusive society.
Framing Digital Mobility Gap: A Starting Point in the Design of Inclusive Mobility Eco-Systems
Authors: Nesterova Nina , Hoeke L. , Goodman-Deane J. A.-L. , Delespaul S. , Wybraniec Bartosz , Lazzarini Boris 
Published: February 2023

AbstractDigital transport eco-systems worldwide provide great advantages to many but also carry a risk of excluding population groups that struggle with accessing or using digital products and services. The DIGNITY project (DIGital traNsport In and for socieTY) delves into the development of such eco-systems to deepen the understanding of the full range of factors that lead to disparities in the uptake of digital transport solutions in Europe. A starting point for developing digitally inclusive transport systems is to obtain state-of-the-art knowledge and understanding of where local transport eco-systems are in relation to the digital gap and digital mobility gap in terms of their policies, transport products and services, and population digital literacy. This chapter presents the methodology developed in the DIGNITY project to frame this digital gap, incorporating a self-assessment framework that may be used by public authorities to identify potential gaps in the development of local digital transport eco-systems. This framework is informed by results from customer journey mapping exercises that provide insights into the daily activities and trips of users, and larger scale surveys on digital technology access, use, attitudes and competence in the area. In the DIGNITY approach as a whole, the results from the framing phase are then used to inform subsequent work on bridging the digital gap through the co-creation of more inclusive policies, products and services. The chapter provides concrete results from the framing exercise in four DIGNITY pilot areas: Barcelona, Tilburg, Flanders and Ancona. The results clearly show that a digital transport gap exists in these areas, and that this is manifested in different ways in different local situations, requiring tailored approaches to address the gap.
Citizen-Centered Mobility Model of Catalonia
Authors: Sanyer Matias Xavier , Alegre Valls Lluís 
Published: February 2023

AbstractThe mobility is becoming ever more complex in a changing environment with the emergence of new means of transport and mobility solutions. In this ecosystem in flux, authorities responsible for mobility must plan for the arrival of such changes, considering the desired mobility model to be attained, one where sustainability, health, digitalisation, and equity, among other aspects, take a prominent role; and all this without disregarding the public, who must be placed at the centre. The digitalisation occurring in society today offers a wide range of solutions; these digital solutions must consider that there is a percentage of the population who are non-digital and that its deployment must the different types of territories, urban and rural.The analysis set out in this article examines the case of the Barcelona Metropolitan Region, describes the characteristics of its citizens from a standpoint of mobility and their acceptance of new trends, identifies existing aims and strategies regarding mobility in the region, and specifically distinguishes the digitalisation strategy in this European region. Finally, this analysis must consider the changes brought about by the COVID-19, in which certain habits have been altered, and where digitalisation has played and will continue to play a sizeable role.