bluuebunny/crossref_metadata_2025_split huggingface dataset:
RNA-Ribo Explorer: interactive mining and visualisation of Ribosome profiling data
Authors: Paulet D. , David A. , Rivals E. 
Published: March 2021

AbstractRNA translation has long been thought as a stable and uniform process by which a ribosome produces a protein encoded by the main Open Reading Frame (ORF) of an mRNA. Recently, growing evidence support incomplete correlation between RNA and protein abundance levels, the existence of alternative ORFs in numerous mammalian RNAs, and the involvement of ribosomes in gene expression regulation, thereby challenging previous views of translation. Ribosome profiling (aka Ribo-seq) has renewed the study of translation by enabling the mapping of translating ribosomes on the whole transcriptome using deep-sequencing.Despite increasing use of Ribo-seq, recent review articles conclude that flexible, interactive tools for mining such data are missing. As Ribo-seq protocols still evolve, flexibility is highly desirable for the end-user. Here we describe RNA-Ribo-Explorer (RRE) a stand-alone tool that fills this gap. With RRE, one can explore read-count profiles of RNAs obtained after mapping, compare them between conditions, and visualize the profiles of individual RNAs. Importantly, the user can mine the data by defining queries that combine several criteria to detect interesting subsets of RNAs. For instance, one can ask RRE to find all RNAs whose translation of UTR region compared to that of the main ORF has changed between two conditions. This feature seems useful for finding candidate RNAs whose translation status or processing has changed across conditions.RRE is a platform independent software and is freely available athttps://gite.lirmm.fr/rivals/RRE/-/releases.
Machine learning models exploring characteristic single-nucleotide signatures in Yellow Fever Virus
Authors: Salgado Álvaro , de Melo-Minardi Raquel C. , Giovanetti Marta , Veloso Adriano , Morais-Rodrigues Francielly , Adelino Talita , de Jesus Ronaldo , Tosta Stephane , Azevedo Vasco , Lourenço Jose , Alcantara Luiz Carlos J. 
Published: March 2021

AbstractYellow fever virus (YFV) is the agent of the most severe mosquito-borne disease in the tropics. Recently, Brazil suffered major YFV outbreaks with a high fatality rate affecting areas where the virus has not been reported for decades, consisting of urban areas where a large number of unvaccinated people live. We developed a machine learning framework combining three different algorithms (XGBoost, random forest and regularized logistic regression). This method was applied to 56 YFV sequences from human infections and 27 from non-human primate (NHPs) infections to investigate the presence of genetic signatures possibly related to disease severity (in human related sequences) and differences in the PCR cycle threshold (Ct) values (in NHP related sequences). Our analyses reveal four non-synonymous single nucleotide variations (SNVs) on sequences from human infections, in proteins NS3 (E614D), NS4a (I69V), NS5 (R727G, V643A) and six non-synonymous SNVs on NHP sequences, in proteins E (L385F), NS1 (A171V), NS3 (I184V) and NS5 (N11S, I374V, E641D). We performed comparative protein structural analysis on these SNVs, describing possible impacts on protein function. Despite the fact that the dataset is limited in size and that this study does not consider virus-host interactions, our work highlights the use of machine learning as a versatile and fast initial approach to genomic data exploration.ImportanceYellow fever is responsible for 29-60 thousand deaths annually in South America and Africa and is the most severe mosquito-borne disease in the tropics. Given the range of clinical outcomes and the availability of YFV genomic data, the use of machine learning analysis promises to be a powerful tool in the investigation of genetic signatures that could impact disease severity and its potential of being reintroduced in an urban transmission cycle. This can assist in the search for biomarkers of severity as well as help elucidating variations in host’s Ct value. This work aims to propose a relatively fast and inexpensive computational analysis framework, which can be used as a real-time, innitial strategy associated with genomic surveillance to identify a set of single nucleotide variants putatively related to biological and clinical characteristics being observed.
The synergic role of actomyosin architecture and biased detachment in muscle energetics: insights in cross bridge mechanism beyond the lever-arm swing
Authors: Marcucci Lorenzo , Fukunaga Hiroki , Yanagida Toshio , Iwaki Mitsuhiro 
Published: March 2021

AbstractMuscle energetics reflects the ability of myosin motors to convert chemical energy into mechanical energy. How this process takes place remains one of the most elusive questions in the field. Here we combined experimental measurements of in vitro sliding velocity based on DNA-origami built filaments carrying myosins with different lever arm length and simulations based on a Monte-Carlo model which accounts for three basic components: (i) the geometrical hindrance, (ii) the mechano-sensing mechanism, and (iii) the biased kinetics for stretched or compressed motors. The model simulations showed that the geometrical hindrance due to acto-myosin spatial mismatching and the preferential detachment of compressed motors are synergic in generating the rapid increase in the ATP-ase rate from isometric to moderate velocities of contraction, thus acting as an energy-conservation strategy in muscle contraction. The velocity measurements on a DNA-origami filament that preserves the motors’ distribution showed that geometrical hindrance and biased detachment generate a non-zero sliding velocity even without rotation of the myosin lever-arm, which is widely recognized as the basic event in muscle contraction. Because biased detachment is a mechanism for the rectification of thermal fluctuations, in the Brownian-ratchet framework, we predict that it requires a non-negligible amount of energy to preserve the second law of thermodynamics. Taken together, our theoretical and experimental results elucidate non-conventional components in the chemo-mechanical energy transduction in muscle.
Effects of domestication on neophobia: A comparison between the domesticated Bengalese finch (Lonchura striata var. domestica) and its wild ancestor, the white-rumped munia (Lonchura striata)
Authors: Suzuki Kenta , Ikebuchi Maki , Kagawa Hiroko , Koike Taku , Okanoya Kazuo 
Published: March 2021

ABSTRACTBengalese finches (Lonchura striatavar.domestica) have more complex song traits than their wild ancestors, white-rumped munias (Lonchura striata). Domesticated finches are likely able to allocate more resources to song development rather than allocating resources to mechanisms aimed at coping with predation, which are no longer needed under domesticated conditions. Here, we aimed to examine the effects of changes in selection pressure due to domestication on the behaviour of Bengalese finches and to contemplate the possible evolutionary mechanisms underlying these changes. To do so, we compared neophobic responses to novel-object conditions as an assessment of reactions to potential predators. We studied groups of Bengalese finches and white-rumped munias and found that Bengalese finches were more likely to eat the food provided to them under novel-object conditions. Bengalese finches had a shorter latency time to eat, and this latency time was less affected by the novel object in the case of Bengalese finches compared to white-rumped munias. Therefore, Bengalese finches have reduced neophobic responses due to domestication. The behavioural strategies of white-rumped munias appear to be more suitable for natural environments, which include unpredictable risks, whereas Bengalese finches have likely adapted their behaviour to the conditions of artificial selection.
3D visualization of SARS-CoV-2 infection and receptor distribution in Syrian hamster lung lobes display distinct spatial arrangements
Authors: Tomris Ilhan , Bouwman Kim M. , Adolfs Youri , Noack Danny , van der Woude Roosmarijn , Herfst Sander , Boons Geert-Jan , Haagmans Bart L. , Pasterkamp R. Jeroen , Rockx Barry , de Vries Robert P. 
Published: March 2021

AbstractSARS-CoV-2 attaches to angiotensin-converting enzyme 2 (ACE2) to gain entry into cells after which the spike protein is cleaved by the transmembrane serine protease 2 (TMPRRS2) to facilitate viral-host membrane fusion. ACE2 and TMPRRS2 expression profiles have been analyzed at the genomic, transcriptomic, and single-cell RNAseq level, however, biologically relevant protein receptor organization in whole tissues is still poorly understood. To describe the organ-level architecture of receptor expression, related to the ability of ACE2 and TMPRRS2 to mediate infectivity, we performed a volumetric analysis of whole Syrian hamster lung lobes. Lung tissue of infected and control animals were stained using antibodies against ACE2 and TMPRRS2, combined with fluorescent spike protein and SARS-CoV-2 nucleoprotein staining. This was followed by light-sheet microscopy imaging to visualize expression patterns. The data demonstrates that infection is restricted to sites with both ACE2 and TMPRRS2, the latter is expressed in the primary and secondary bronchi whereas ACE2 is predominantly observed in the terminal bronchioles and alveoli. Conversely, infection completely overlaps at these sites where ACE2 and TMPRSS2 co-localize.
Neural markers of speech comprehension: measuring EEG tracking of linguistic speech representations, controlling the speech acoustics
Authors: Gillis Marlies , Vanthornhout Jonas , Simon Jonathan Z. , Francart Tom , Brodbeck Christian 
Published: March 2021

AbstractWhen listening to speech, our brain responses time-lock to acoustic events in the stimulus. Recent studies have also reported that cortical responses track linguistic representations of speech. However, tracking of these representations is often described without controlling for acoustic properties. Therefore, the response to these linguistic representations might reflect unaccounted acoustic processing rather than language processing. Here, we evaluated the potential of several recently proposed linguistic representations as neural markers of speech comprehension. To do so, we investigated EEG responses to audiobook speech of 29 participants (22 ♀). We examined whether these representations contribute unique information over and beyond acoustic neural tracking and each other. Indeed, not all of these linguistic representations were significantly tracked after controlling for acoustic properties. However, phoneme surprisal, cohort entropy, word surprisal, and word frequency were all significantly tracked over and beyond acoustic properties. We also tested the generality of the associated responses by training on one story and testing on another. In general, the linguistic representations are tracked similarly across different stories spoken by different readers. These results suggests that these representations characterize processing of the linguistic content of speech.Significance StatementFor clinical applications it would be desirable to develop a neural marker of speech comprehension derived from neural responses to continuous speech. Such a measure would allow for behaviour-free evaluation of speech understanding; this would open doors towards better quantification of speech understanding in populations from whom obtaining behavioral measures may be difficult, such as young children or people with cognitive impairments, to allow better targeted interventions and better fitting of hearing devices.
The wrong side of the spreadsheets: a life in the digital humanities
Authors: Anderson Janet 
Published: March 2021

Purpose
The purpose of this viewpoint paper is to reflect on both the technological and the humanities aspects of working in the digital humanities.

Design/methodology/approach
The author completed her academic career as Professor of Digital Humanities (DH) at the University of Brighton, UK. In terms of approach, she looks back over 25 years of working in this domain, which she entered as a scientist in contrast to most of the other academics at that time who came from the humanities. She delineates her academic journey that passed through various disciplines/fields.

Findings
The author reflects upon her entire career, starting with decisions made at school, to see how they have affected her contribution to DH. She concludes that a deep understanding of technological issues is fundamental to making sense of such complex fields as Big Data and its effect on humanities research in particular and society in general. She also draws attention to the loss of several highly technical, specialised and practical DH teams, which were replaced with ones whose focus is on DH discourse.

Originality/value
The author is writing as one of the very few scientists who belonged to the new area of history and computing in the mid-1990s.
On distance measure and TOPSIS model for probabilistic interval-valued hesitant fuzzy sets: application to healthcare facilities in public hospitals
Authors: Ali Jawad , Bashir Zia , Rashid Tabasam 
Published: March 2021

PurposeThe purpose of the development of the paper is to construct probabilistic interval-valued hesitant fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model and to improve some preliminary aggregation operators such as probabilistic interval-valued hesitant fuzzy averaging (PIVHFA) operator, probabilistic interval-valued hesitant fuzzy geometric (PIVHFG) operator, probabilistic interval-valued hesitant fuzzy weighted averaging (PIVHFWA) operator, probabilistic interval-valued hesitant fuzzy ordered weighted averaging (PIVHFOWA) operator, probabilistic interval-valued hesitant fuzzy weighted geometric (PIVHFWG) operator and probabilistic interval-valued hesitant fuzzy ordered weighted geometric (PIVHFOWG) operator to cope with multicriteria group decision-making (MCGDM) problems in an efficient manner.Design/methodology/approach(1) To design probabilistic interval-valued hesitant fuzzy TOPSIS model. (2) To improve some of the existing aggregation operators. (3) To propose the Hamming distance, Euclidean distance, Hausdorff distance and generalized distance between probabilistic interval-valued hesitant fuzzy sets (PIVHFSs).FindingsThe results of the proposed model are discussed in comparison with the aggregation-based method from the related literature and found the effectiveness of the proposed model and improved aggregation operators.Practical implicationsA case study concerning the healthcare facilities in public hospital is addressed.Originality/valueThe notion of the proposed distance measure is used as rational tool to extend TOPSIS model for probabilistic interval-valued hesitant fuzzy setting.
Cybersecurity advocates: discovering the characteristics and skills of an emergent role
Authors: Haney Julie M. , Lutters Wayne G. 
Published: March 2021

PurposeCybersecurity advocates safeguard their organizations by promoting security best practices. This paper aims to describe the skills and characteristics of successful advocates.Design/methodology/approachThis study involved 28 in-depth interviews of cybersecurity advocates.FindingsEffective advocates possess not only technical acumen but also interpersonal skills, communication skills context awareness and a customer service orientation.Practical implicationsNon-technical skills are deemphasized in cybersecurity training, limiting career progression into the cybersecurity advocate role for existing security professionals and those from other disciplines. This paper suggests improvements for professional development that encourage greater security workforce diversity.Originality/valueTo the best of the authors’ knowledge, this study is the first to define and enumerate competencies for the role of cybersecurity advocate.
Rethinking academic library space amidst the COVID-19 pandemic in South Africa: preparing for the future
Authors: Chisita Collence Takaingenhamo , Chizoma Ukwoma Scholastica 
Published: March 2021

PurposeAcademic libraries’ response to the Coronavirus disease (COVID-19) pandemic might be an opportunity to reassert and reemphasise their roles in the national disaster management matrix. The purpose of this study is to review the responses of academic libraries in South Africa during the COVID-19 pandemic. The global outbreak of COVID-19 has precipitated a challenge amongst all institutions, communities and libraries as evidenced by the growing lockdowns, deaths and shocking statistics of infections. This has triggered a fundamental need to rethink how libraries can establish innovative ways to continue providing services to users.Design/methodology/approachThis study adopted the interpretive research paradigm to review the situation in South Africa in response to the COVID-19 pandemic. The study used an analysis of secondary sources, the activities that took place and personal experience to answer the research questions.FindingsThe analysis showed that academic libraries and publishers have risen to the occasion, offering more free content and curating personalised collections so that citizens can have uninterrupted access to content and learning. The digital libraries in South Africa are considered vital alleyways to high-quality e-books, journals and educational content, including open educational resources. Digital library services have enabled academic libraries in South Africa to excel in providing online services, therefore ensuring that learning, research and teaching continued.Originality/valueThis study, using Habermas’s idea of the public sphere as a fundamental theoretical framework, notes that when the physical space is closed, it is necessary for academic libraries in South Africa to make use of the digital space. This study will contribute to the corpus of knowledge relating to South African digital libraries’ response to the COVID-19 pandemic.
Intention to adopt pro-environmental behaviors among university students of hard and soft sciences: the case of drinking by reusable bottles
Authors: Fedi Angela , La Barbera Francesco , De Jong Annabelle , Rollero Chiara 
Published: March 2021

Purpose
The market of bottled water is one of the largest in the world. Paradoxically, the consumption of water in plastic bottles is highest in countries rich in the potable tap water of excellent quality. This paper aims to gain a better understanding of the factors that foster or hinder the intention to use refillable water bottles by university students and to determine whether their study program played a moderating role.

Design/methodology/approach
Within the framework of Ajzen’s theory of planned behavior (TPB), this paper conducted this cross-sectional study to understand the influence of attitudes, norms and perceived behavioral control (PBC) on the intention to drink tap water from reusable bottles. Italian university students (n = 540) majoring in the hard (42.4%) or the soft (57.6%) sciences completed an anonymous self-report questionnaire.

Findings
For both groups, there was a significant association between attitudes and intention to use a refillable water bottle. The intention to drink tap water was also influenced by PBC among the hard science students, whereas among the soft science students the descriptive norm exerted a significant influence.

Originality/value
This is the first application of TPB, a well-established theoretical and methodological framework, to understand the intention of university students to drink tap water from reusable bottles. Within the framework of TPB, this study is the first to address this specific pro-environmental behavior and explore the potential moderating role of university studies programs, which proved significant.
Comparative CSR decision-making in the Middle East: an exploratory study
Authors: El Haddad Pierre , Bachkirov Alexandre Anatolievich , Grishina Olga 
Published: March 2021

Purpose
This study aims to explore the commonalities and differences of corporate social responsibility (CSR) perceptions among business leaders in Oman and Lebanon, two Middle Eastern countries forming a comparative dyad with a high level of cultural variance within the Arab cluster.

Design/methodology/approach
Semi-structured interviews were used to elicit qualitative data that were analyzed by means of multilevel analysis.

Findings
The findings provide empirical evidence that CSR is a powerful factor in managerial decision-making in the Middle East with the national cultures of Oman and Lebanon exerting partially differing effects on CSR decision-making.

Practical implications
The study enlightens practicing managers and policymakers in terms of the salience of multiple actors’ influence on CSR decision-making processes and the responses they may receive when developing and implementing CSR initiatives in the Middle East.

Originality/value
The study proposes a seven nodal model, which captures the flow of CSR decision-making in the research contexts.
Flexible learning with multicomponent blended learning mode for undergraduate chemistry courses in the pandemic of COVID-19
Authors: Lo Chui-Man , Han Jie , Wong Emily S.W. , Tang Chin-Cheung 
Published: March 2021

Purpose
This paper aims to report a case study in flexible learning with multicomponent blended learning mode in an undergraduate chemistry course. Traditional chemistry courses usually include lectures, tutorials and laboratory sections. For a course “Advances in Organic Synthesis” at undergraduate level, it consists of advanced information in organic chemistry such as reaction mechanisms, asymmetric catalysis, retrosynthesis and applications in synthesis of natural products. This course is a difficult subject and requires deep understanding of contents. After learning this course, students should have comprehensive knowledge in advanced strategies of organic synthesis and have an ability to apply them to real cases. This “flexible learning with multicomponent blended learning mode” was implemented by the authors to enhance student engagement and self-motivation in their studies.

Design/methodology/approach
The authors hoped to enhance students’ engagement in “flexible learning” – a mixed concept with “blended learning” and “flipped classroom” – and called this approach as “multicomponent blended learning mode.” Blended learning combines face-to-face and e-learning components with interactive Web-based components and technical experimental videos were developed. The knowledge integrated in different components provides a natural environment to link the different synthetic methods together, which help students to get a better understanding of the complicated knowledge and strengthen their skills. For flipped classroom, students participated in the case studies of the organic synthesis and shared their findings to other classmates in oral presentations.

Findings
In this study, both course evaluation score and students’ academic performance in the “multicomponent blended learning mode” were increased significantly when comparing with traditional teaching methods in 2011. It was found that students’ engagement and their self-motivation in learning were enhanced.

Originality/value
The positive feedback from the students and the enhancement of their academic performance supported the value in this research. Besides, most universities in Hong Kong have suspended all face-to-face classes and conducted all teaching in online mode during COVID-19 outbreak. As the multicomponent blended learning mode of this course has already been conducted for eight cohorts, the authors are confident that this feature can minimize the sudden change in the learning habits for the students. As social factors and individual variations in students’ learning and study mode may affect the learning outcomes, these interactive multicomponent e-learning components in this special period make students excited when they can study and digest the knowledge according to their own pace.