bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a bipolar electrostatic chuck with a compliant beam-array assembly having four 3D-printed layers for large film handling
Authors: Taoka Yuki , Hayashi Terumichi , Hemthavy Pasomphone , Takahashi Kunio , Saito Shigeki 
Published: January 2022

Abstract
This study proposes and verifies bipolar electrostatic grippers stacking 3D-printed-layered modules consisting of arrays of elastically deformable bipolar beams. The influence of the mechanical compliance of grippers on the attractive force that it generates is clarified by comparing two types of modules having either high or low mechanical compliances. Experiments measured the attractive force of the gripper and demonstrated the pick-and-place performance of a thin film. The results show that mechanical compliance plays an important role in mitigating the attractive force decrease in stacking modules. The grippers’ ability for thin film handling is demonstrated by observing pick-and-place behaviours of the proposed bipolar electrostatic grippers.
Evaluation of the potential of nanofluids containing different Ag nanoparticle size distributions for enhanced solar energy conversion in hybrid photovoltaic-thermal (PVT) applications
Authors: Walshe J , Doran J , Amarandei G 
Published: January 2022

Abstract
Hybridising photovoltaic and photothermal technologies into a single system that can simultaneously deliver heat and power represents one of the leading strategies for generating clean energy at more affordable prices. In a hybrid photovoltaic-thermal (PVT) system, the capability to modulate the thermal and electrical power output is significantly influenced by the spectral properties of the heat transfer fluid utilised. In this study, we report on one of the first experimental evaluations of the capability of a multimodal silver nanofluid containing various particle shapes and particle sizes to selectively modulate the solar energy for PVT applications. The diverse set of particle properties led up to a 50.4% enhancement in the solar energy absorbed by the nanofluid over the 300 nm—550 nm spectral region, where silicon is known to exhibit poor photovoltaic conversion performances. This improved substantially the absorption of solar energy, with an additional 18–129 W m−2 of thermal power being generated by the PVT system. Along with the advancements made in the thermal power output of the PVT system, a decrease of 4.7–36.6 W m−2 in the electrical power generated by the photovoltaic element was noted. Thus, for every ∼11 W m−2 increase of thermal power achieved through the addition of the nanoparticles, a reduction of ∼3 W m−2 in the ability to generate clean electricity was sustained by the PVT. Despite the energy trade-offs involved under the conditions of the nanofluid, the PVT system cumulatively harvested 405 W m−2 of solar energy, which amounts to a total conversion efficiency of 45%. Furthermore, the economics of the additional energy harvested through merging of the two systems was found to reach an enhancement of 77% under certain European conditions.
CRAFT: a bioinformatics software for custom prediction of circular RNA functions
Authors: Dal Molin Anna , Gaffo Enrico , Difilippo Valeria , Buratin Alessia , Tretti Parenzan Caterina , Bresolin Silvia , Bortoluzzi Stefania 
Published: January 2022

Abstract
Circular RNAs (circRNAs), transcripts generated by backsplicing, are particularly stable and pleiotropic molecules, whose dysregulation drives human diseases and cancer by modulating gene expression and signaling pathways. CircRNAs can regulate cellular processes by different mechanisms, including interaction with microRNAs (miRNAs) and RNA-binding proteins (RBP), and encoding specific peptides. The prediction of circRNA functions is instrumental to interpret their impact in diseases, and to prioritize circRNAs for functional investigation. Currently, circRNA functional predictions are provided by web databases that do not allow custom analyses, while self-standing circRNA prediction tools are mostly limited to predict only one type of function, mainly focusing on the miRNA sponge activity of circRNAs. To solve these issues, we developed CRAFT (CircRNA Function prediction Tool), a freely available computational pipeline that predicts circRNA sequence and molecular interactions with miRNAs and RBP, along with their coding potential. Analysis of a set of circRNAs with known functions has been used to appraise CRAFT predictions and to optimize its setting. CRAFT provides a comprehensive graphical visualization of the results, links to several knowledge databases, and extensive functional enrichment analysis. Moreover, it originally combines the predictions for different circRNAs. CRAFT is a useful tool to help the user explore the potential regulatory networks involving the circRNAs of interest and generate hypotheses about the cooperation of circRNAs into the modulation of biological processes.
Ontology-aware neural network: a general framework for pattern mining from microbiome data
Authors: Zha Yuguo , Ning Kang 
Published: January 2022

AbstractWith the rapid accumulation of microbiome data around the world, numerous computational bioinformatics methods have been developed for pattern mining from such paramount microbiome data. Current microbiome data mining methods, such as gene and species mining, rely heavily on sequence comparison. Most of these methods, however, have a clear trade-off, particularly, when it comes to big-data analytical efficiency and accuracy. Microbiome entities are usually organized in ontology structures, and pattern mining methods that have considered ontology structures could offer advantages in mining efficiency and accuracy. Here, we have summarized the ontology-aware neural network (ONN) as a novel framework for microbiome data mining. We have discussed the applications of ONN in multiple contexts, including gene mining, species mining and microbial community dynamic pattern mining. We have then highlighted one of the most important characteristics of ONN, namely, novel knowledge discovery, which makes ONN a standout among all microbiome data mining methods. Finally, we have provided several applications to showcase the advantage of ONN over other methods in microbiome data mining. In summary, ONN represents a paradigm shift for pattern mining from microbiome data: from traditional machine learning approach to ontology-aware and model-based approach, which has found its broad application scenarios in microbiome data mining.
IndGOterm: a qualitative method for the identification of individually dysregulated GO terms in cancer
Authors: Zhang Jiashuai , Xiao Huiting , Song Kai , Li Keru , Yuan Hengrui , Yuan Rongqiang , Yang Jia , Zhao Yuting , Chang Zhiqiang , Zhao Wenyuan 
Published: January 2022

Abstract
Individual pathway analysis can dissect heterogeneities among different cancer patients and provide efficient guidelines for individualized therapy. However, the existence of the batch effect brings extensive limitations for the application of many individual methods for pathway analysis. Previously, researchers proposed that methods based on within-sample relative expression ordering (REO) of the genes are notably insensitive to ‘batch effects’. In this article, we focus on the Gene Ontology (GO) database and propose an individual qualitative GO term analysis method (IndGOterm) based on the REO of genes. Compared with some current widely used single-sample enrichment analysis methods, such as ssGSEA and GSVA, IndGOterm has a predominance of ignoring the batch effects caused by diverse technologies. Through the survival and drug responses analysis, we found IndGOterm could capture more terms connected to cancer than other single-sample enrichment analysis methods. Furthermore, through the application of IndGOterm, we found some terms that present different dysregulation models that manifest heterogenetic in homologous patients. Collectively, these results attested that IndGOterm could capture useful information from patients and be a useful tool to reveal the intrinsic characteristic of cancer. An open-source R statistical analysis package ‘IndGOterm’ is available at https://github.com/robert19960424/IndGOterm.
An accurate method for identifying recent recombinants from unaligned sequences
Authors: Feng Qian , Tiedje Kathryn E , Ruybal-Pesántez Shazia , Tonkin-Hill Gerry , Duffy Michael F , Day Karen P , Shim Heejung , Chan Yao-Ban 
Published: January 2022

Abstract

Motivation
Recombination is a fundamental process in molecular evolution, and the identification of recombinant sequences is thus of major interest. However, current methods for detecting recombinants are primarily designed for aligned sequences. Thus, they struggle with analyses of highly diverse genes, such as the var genes of the malaria parasite Plasmodium falciparum, which are known to diversify primarily through recombination.

Results
We introduce an algorithm to detect recent recombinant sequences from a dataset without a full multiple alignment. Our algorithm can handle thousands of gene-length sequences without the need for a reference panel. We demonstrate the accuracy of our algorithm through extensive numerical simulations; in particular, it maintains its effectiveness in the presence of insertions and deletions. We apply our algorithm to a dataset of 17 335 DBLα types in var genes from Ghana, observing that sequences belonging to the same ups group or domain subclass recombine amongst themselves more frequently, and that non-recombinant DBLα types are more conserved than recombinant ones.

Availability and implementation
Source code is freely available at https://github.com/qianfeng2/detREC_program.

Supplementary information
Supplementary data are available at Bioinformatics online.
Anti-TNF Agents Restrict Adherent-invasive Escherichia coli Replication Within Macrophages Through Modulation of Chitinase 3-like 1 in Patients with Crohn’s Disease
Authors: Douadi Clara , Vazeille Emilie , Chambon Christophe , Hébraud Michel , Fargeas Margot , Dodel Marie , Coban Dilek , Pereira Bruno , Birer Aurélien , Sauvanet Pierre , Buisson Anthony , Barnich Nicolas 
Published: January 2022

Abstract

Background and Aims
The mechanism of action of anti-tumour necrosis factor [anti-TNF] agents could implicate macrophage modulation in Crohn’s disease [CD]. As CD macrophages are defective in controlling CD-associated adherent-invasive Escherichia coli [AIEC], anti-TNF agents could limit AIEC replication within macrophages. We assessed the effect of anti-TNF agents on AIEC survival within monocyte-derived macrophages [MDMs] from CD patients and attempted to identify the proteins involved.

Methods
Peripheral blood MDMs were obtained from 44 CD patients [22 with and 22 without anti-TNF agents]. MDMs were infected with reference strain AIEC-LF82. Proteomic analysis was performed before and 6 h after AIEC-LF82 infection.

Results
AIEC-LF82 survival was lower in MDMs from CD patients receiving anti-TNF agents compared to those who did not [−73%, p = 0.006]. After AIEC-LF82 infection, the levels of CD82 [p = 0.007], ILF3 [Interleukin enhancer-binding factor 3; p = 0.001], FLOT-1 [Flotillin-1; p = 0.007] and CHI3L1 [Chitinase 3-like 1; p = 0.035] proteins were different within CD-MDMs depending on anti-TNF exposure. FLOT-1 [ϱ = −0.44; p = 0.038] and CHI3L1 [ϱ = 0.57, p = 0.006] levels were inversely and positively correlated with AIEC survival within MDMs from CD patients with or without anti-TNF, respectively. We observed a dose-dependent decrease of AIEC-LF82 survival after adjunction of anti-TNF within MDMs, inducing an increase of FLOT-1 and decrease of CHI3L1 mRNA levels. Neutralization of intra-macrophagic CHI3L1 protein using anti-CHI3L1 antibodies reduced AIEC survival within macrophages 6 h after infection [p &lt; 0.05].

Conclusion
Anti-TNF agents are able to restrict replication of pathobionts, such as AIEC, within macrophages by modulating FLOT-1 and CHI3L1 expression in CD patients.
Indications and outcomes of cardiac catheterization following congenital heart surgery in children
Authors: Haddad Raymond N , Lange Juan Manuel , Raisky Olivier , Gaudin Regis , Barbanti Claudio , Bonnet Damien , Malekzadeh-Milani Sophie 
Published: January 2022

AbstractOBJECTIVESOur goal was to evaluate the indications for postoperative cardiac catheterizations after paediatric cardiac surgeries and their impact on outcomes.METHODSNon-planned cardiac catheterizations performed after congenital heart surgeries and before discharge between January 2013 and July 2019 were reviewed. Hybrid procedures were excluded. Heart defects, illness course, surgeries and catheter procedures were classified. Indications and findings were comprehensively regrouped. Outcomes were analysed.RESULTSCardiac catheterizations were performed on 192 patients (median age 2.3 months, weight 4.2 kg) on median postoperative day 7 (interquartile range, 2–17 days). Patients had defects of great complexity (79.9%), high disease severity index (46.4%), high Aristotle level of surgical complexity (75%) and a high Catheterization RISk Score for Pediatrics category of catheterizations (61%). Catheterizations confirmed 66% of suspected diagnoses. Confirmed diagnoses were more likely to be haemodynamic anomalies than anatomical lesions (81.3% &gt; 53.7%, P &lt; 0.001). Confirmed anatomical lesions were more likely to be residual than new lesions created by surgery (88.5% &gt; 40.4%, P &lt; 0.001). New diagnoses were identified in 36.5% of patients. Catheterization findings led to catheter-based or surgical interventions in 120 (62.5%) patients. Transcatheter interventions were successful (97.7%), immediate (89.5%) and performed across fresh suture lines (27.8%). Repeat catheterizations (76% interventional) were necessary in 25 (13%) patients. A high index of disease severity [odds ratio (OR): 16.26, 95% confidence interval (CI): 3.72–71.17], extracorporeal membrane oxygenation support (OR: 10.35, 95% CI: 2.78–38.56), delayed sternal closure (OR: 4.66, 95% CI: 1.25–17.32) and surgically acquired lesions (OR: 3.70, 95% CI: 1.22–11.16) were significant risk factors of 12-month mortality.CONCLUSIONSPostoperative cardiac catheterizations answer both anatomical and haemodynamic questions in high-risk patients with complicated courses and guide subsequent treatment with satisfactory outcomes.
Preoperative risk assessment tools for morbidity after cardiac surgery: a systematic review
Authors: Sanders Julie , Makariou Nicole , Tocock Adam , Magboo Rosalie , Thomas Ashley , Aitken Leanne M 
Published: January 2022

Abstract

Background
Postoperative morbidity places considerable burden on health and resources. Thus, strategies to identify, predict, and reduce postoperative morbidity are needed.

Aims
To identify and explore existing preoperative risk assessment tools for morbidity after cardiac surgery.

Methods
Electronic databases (including MEDLINE, CINAHL, and Embase) were searched to December 2020 for preoperative risk assessment models for morbidity after adult cardiac surgery. Models exploring one isolated postoperative morbidity and those in patients having heart transplantation or congenital surgery were excluded. Data extraction and quality assessments were undertaken by two authors.

Results
From 2251 identified papers, 22 models were found. The majority (54.5%) were developed in the USA or Canada, defined morbidity outcome within the in-hospital period (90.9%), and focused on major morbidity. Considerable variation in morbidity definition was identified, with morbidity incidence between 4.3% and 52%. The majority (45.5%) defined morbidity and mortality separately but combined them to develop one model, while seven studies (33.3%) constructed a morbidity-specific model. Models contained between 5 and 50 variables. Commonly included variables were age, emergency surgery, left ventricular dysfunction, and reoperation/previous cardiac surgery, although definition differences across studies were observed. All models demonstrated at least reasonable discriminatory power [area under the receiver operating curve (0.61–0.82)].

Conclusion
Despite the methodological heterogeneity across models, all demonstrated at least reasonable discriminatory power and could be implemented depending on local preferences. Future strategies to identify, predict, and reduce morbidity after cardiac surgery should consider the ageing population and those with minor and/or multiple complex morbidities.
On Modified Scattering for 1D Quadratic Klein–Gordon Equations With Non-Generic Potentials
Authors: Lindblad Hans , Lührmann Jonas , Schlag Wilhelm , Soffer Avy 
Published: January 2022

AbstractWe consider the asymptotic behavior of small global-in-time solutions to a 1D Klein–Gordon equation with a spatially localized, variable coefficient quadratic nonlinearity and a non-generic linear potential. The purpose of this work is to continue the investigation of the occurrence of a novel modified scattering behavior of the solutions that involves a logarithmic slow-down of the decay rate along certain rays. This phenomenon is ultimately caused by the threshold resonance of the linear Klein–Gordon operator. It was previously uncovered for the special case of the zero potential in [51]. The Klein–Gordon model considered in this paper is motivated by the asymptotic stability problem for kink solutions arising in classical scalar field theories on the real line.
Combining failure modes and effects analysis and cause–effect analysis: a novel method of risk analysis to reduce anaphylaxis due to contrast media
Authors: Koike Daisuke , Yamakami Junichi , Miyashita Terumi , Kataoka Yumi , Nishida Hiroshi , Hattori Hidekazu , Yasuda Ayuko 
Published: January 2022

AbstractBackgroundContrast media agents are essential for computed tomography (CT)-based diagnoses. However, they can cause fatal adverse effects such as anaphylaxis in patients. Although it is rare, the chances of anaphylaxis increase with the number of examinations.ObjectiveWe aimed to design a quality improvement initiative to reduce patient risk to contrast media agents.MethodsWe analysed CT processes using contrast iodine in a tertiary-care academic hospital that performs approximately 14 000 CT scans per year in Japan. We applied a combination of failure modes and effects analysis (FMEA) and cause–effect analysis to reduce the risk of patients developing allergic reactions to iodine-based contrast agents during CT imaging.ResultsOur multidisciplinary team comprising seven professionals analysed the data and designed a 56-process flowchart of CT imaging with iodine. We obtained 177 failure modes, of which 15 had a risk-probability number higher than 100. We identified the two riskiest processes and developed cause-and-effect diagrams for both: one was related to the exchange of information between the radiation and hospital information system regarding the patient’s allergy, the other was due to education and structural deficiencies in observation following the exam.ConclusionThe combined method of FMEA and cause-and-effect analysis reveals high-risk processes and suggests measures to reduce these risks. FMEA is not well-known in healthcare but has significant potential for improving patient safety. Our findings emphasise the importance of adopting new techniques to reduce patient risk and carry out best practices in radiology.
Seeing All Evil: The Global Cruelty of Digital Visibility
Authors: Austin Jonathan Luke 
Published: January 2022

Abstract
Cruelty is a historical constant across world politics. Nonetheless, something has changed. Today, it is possible to observe death, massacre, torture, police brutality, terrorist attacks, drone strikes, and more, in high-definition video. Sometimes, we can watch live. In this article, I ask what it means when the historical sanitization of cruelty, injustice, and violence is stripped away. I do so in three ways. First, I explore how digital media has transformed how knowledge of violence is produced, circulates, and affects those who witness it. I focus in particular on how this visibility of cruelty affectively fractures our ontological security, undermines societal solidarity, and amplifies polarization. Second, I describe how this process is marked by substantive global inequalities vis-à-vis who is “protected” (or not) from exposure to graphic imagery. Third, I ground my discussion empirically through participant observation conducted with members of the militia group Hezbollah that focused on their emotional, affective, discursive, and political reactions to watching videos circulating on social media depicting members of their own group committing war crimes in Syria. The article concludes by dwelling on the worrying possible political futures these dynamics appear to be opening up.
The Role of Disclosure in Green Finance
Authors: Steuer Sebastian , Tröger Tobias H 
Published: January 2022

ABSTRACT
In this article, we study the design features of disclosure regulations that seek to trigger the green transition of the global economy and ask whether such interventions are likely to bring about sufficient market discipline to achieve socially optimal climate targets. Transparency obligations stipulated in green finance regulation can be categorized as either compelling the standardized disclosure of raw data, or providing quality labels that signal desirable green characteristics of investment products based on a uniform methodology. Both categories of transparency requirements can be imposed at activity, issuer, and portfolio level. Finance theory and empirical evidence suggest that investors may prefer ‘green’ over ‘dirty’ assets for both financial and non-financial reasons and may thus demand higher returns from environmentally harmful investment opportunities. Investor-led market discipline can benefit from mandatory transparency requirements and their rigid (public) enforcement, because these requirements prevent an underproduction of standardized high-quality information. However, many forces and frictions may also steer market outcomes away from socially optimal equilibria aligned with climate targets. Disclosure-centred green finance legislation is a second best to more direct forms of regulatory intervention (eg global emissions trading), but can play a supporting role in the sustainable transition, especially while first-best solutions remain politically unavailable.