bluuebunny/crossref_metadata_2025_split huggingface dataset:
3D Printing for Cardiovascular Applications: From End-to-End Processes to Emerging Developments
Authors: Gharleghi Ramtin , Dessalles Claire A. , Lal Ronil , McCraith Sinead , Sarathy Kiran , Jepson Nigel , Otton James , Barakat Abdul I. , Beier Susann 
Published: May 2021

Abstract3D printing as a means of fabrication has seen increasing applications in medicine in the last decade, becoming invaluable for cardiovascular applications. This rapidly developing technology has had a significant impact on cardiovascular research, its clinical translation and education. It has expanded our understanding of the cardiovascular system resulting in better devices, tools and consequently improved patient outcomes. This review discusses the latest developments and future directions of generating medical replicas (‘phantoms’) for use in the cardiovascular field, detailing the end-to-end process from medical imaging to capture structures of interest, to production and use of 3D printed models. We provide comparisons of available imaging modalities and overview of segmentation and post-processing techniques to process images for printing, detailed exploration of latest 3D printing methods and materials, and a comprehensive, up-to-date review of milestone applications and their impact within the cardiovascular domain across research, clinical use and education. We then provide an in-depth exploration of future technologies and innovations around these methods, capturing opportunities and emerging directions across increasingly realistic representations, bioprinting and tissue engineering, and complementary virtual and mixed reality solutions. The next generation of 3D printing techniques allow patient-specific models that are increasingly realistic, replicating properties, anatomy and function.
Mean-Field Models for EEG/MEG: From Oscillations to Waves
Authors: Byrne Áine , Ross James , Nicks Rachel , Coombes Stephen 
Published: May 2021

AbstractNeural mass models have been used since the 1970s to model the coarse-grained activity of large populations of neurons. They have proven especially fruitful for understanding brain rhythms. However, although motivated by neurobiological considerations they are phenomenological in nature, and cannot hope to recreate some of the rich repertoire of responses seen in real neuronal tissue. Here we consider a simple spiking neuron network model that has recently been shown to admit an exact mean-field description for both synaptic and gap-junction interactions. The mean-field model takes a similar form to a standard neural mass model, with an additional dynamical equation to describe the evolution of within-population synchrony. As well as reviewing the origins of this next generation mass model we discuss its extension to describe an idealised spatially extended planar cortex. To emphasise the usefulness of this model for EEG/MEG modelling we show how it can be used to uncover the role of local gap-junction coupling in shaping large scale synaptic waves.
Brand as Promise
Authors: Bhargava Vikram R. , Bedi Suneal 
Published: May 2021

AbstractBrands are widely regarded as a constellation of shared associations surrounding a company and its offerings. On the traditional view of brands, these associations are regarded as perceptions and attitudes in consumers’ minds in relation to a company. We argue that this traditional framing of brands faces an explanatory problem: the inability to satisfactorily explain why certain branding activism initiatives elicit the moralized reactive attitudes that are paradigmatic responses to wrongdoing. In this paper, we argue for a reframing of brands that calls for viewing brands as a series of normatively binding expectations that are ethically akin to promises. Our promissory framing of brands avoids the explanatory problem, illuminates a number of ethical requirements on branding, and reconceptualizes the role of brand managers.
Blockchain for decentralization of internet: prospects, trends, and challenges
Authors: Zarrin Javad , Wen Phang Hao , Babu Saheer Lakshmi , Zarrin Bahram 
Published: May 2021

AbstractBlockchain has made an impact on today’s technology by revolutionizing the financial industry through utilization of cryptocurrencies using decentralized control. This has been followed by extending Blockchain to span several other industries and applications for its capabilities in verification. With the current trend of pursuing the decentralized Internet, many methods have been proposed to achieve decentralization considering different aspects of the current Internet model ranging from infrastructure and protocols to services and applications. This paper investigates Blockchain’s capacities to provide a robust and secure decentralized model for Internet. The paper conducts a critical review on recent Blockchain-based methods capable for the decentralization of the future Internet. We identify and investigate two research aspects of Blockchain that provides high impact in realizing the decentralized Internet with respect to current Internet and Blockchain challenges while keeping various design in considerations. The first aspect is the consensus algorithms that are vital components for decentralization of the Blockchain. We identify three key consensus algorithms including PoP, Paxos, and PoAH that are more adequate for reaching consensus for such tremendous scale Blockchain-enabled architecture for Internet. The second aspect that we investigated is the compliance of Blockchain with various emerging Internet technologies and the impact of Blockchain on those technologies. Such emerging Internet technologies in combinations with Blockchain would help to overcome Blockchain’s established flaws in a way to be more optimized, efficient and applicable for Internet decentralization.
Young People as Drivers or Inhibitors of the Sustainability Movement: The Case of Anti-Consumption
Authors: Ziesemer F. , Hüttel A. , Balderjahn I. 
Published: May 2021

AbstractAs overconsumption has negative effects on ecological balance, social equality, and individual well-being, reducing consumption levels among the materially affluent is an emerging strategy for sustainable development. Today’s youth form a crucial target group for intervening in unsustainable overconsumption habits and for setting the path and ideas on responsible living. This article explores young people’s motivations for engaging in three behavioural patterns linked to anti-consumption (voluntary simplicity, collaborative consumption, and living within one’s means) in relation to sustainability. Applying a qualitative approach, laddering interviews reveal the consequences and values behind the anti-consumption behaviours of young people of ages 14 to 24 according to a means-end chains analysis. The findings highlight potential for and the challenges involved in motivating young people to reduce material levels of consumption for the sake of sustainability. Related consumer policy tools from the fields of education and communication are identified. This article provides practical implications for policy makers, activists, and educators. Consumer policies may strengthen anti-consumption among young people by addressing individual benefits, enabling reflection on personal values, and referencing credible narratives. The presented insights can help give a voice to young consumers, who struggle to establish themselves as key players in shaping the future consumption regime.
The local dark sector
Authors: Bergé Joel , Baudis Laura , Brax Philippe , Chiow Sheng-Wey , Christophe Bruno , Doré Olivier , Fayet Pierre , Hees Aurélien , Jetzer Philippe , Lämmerzahl Claus , List Meike , Métris Gilles , Pernot-Borràs Martin , Read Justin , Reynaud Serge , Rhodes Jason , Rievers Benny , Rodrigues Manuel , Sumner Timothy , Uzan Jean-Philippe , Yu Nan 
Published: May 2021

AbstractWe speculate on the development and availability of new innovative propulsion techniques in the 2040s, that will allow us to fly a spacecraft outside the Solar System (at 150 AU and more) in a reasonable amount of time, in order to directly probe our (gravitational) Solar System neighborhood and answer pressing questions regarding the dark sector (dark energy and dark matter). We identify two closely related main science goals, as well as secondary objectives that could be fulfilled by a mission dedicated to probing the local dark sector: (i) begin the exploration of gravitation’s low-acceleration regime with a spacecraft and (ii) improve our knowledge of the local dark matter and baryon densities. Those questions can be answered by directly measuring the gravitational potential with an atomic clock on-board a spacecraft on an outbound Solar System orbit, and by comparing the spacecraft’s trajectory with that predicted by General Relativity through the combination of ranging data and the in-situ measurement (and correction) of non-gravitational accelerations with an on-board accelerometer. Despite a wealth of new experiments getting online in the near future, that will bring new knowledge about the dark sector, it is very unlikely that those science questions will be closed in the next two decades. More importantly, it is likely that it will be even more urgent than currently to answer them. Tracking a spacecraft carrying a clock and an accelerometer as it leaves the Solar System may well be the easiest and fastest way to directly probe our dark environment.
Bridging the Digital Divide in Ethnic Minority Older Adults: an Organisational Qualitative Study
Authors: Choudrie Jyoti , Zamani Efpraxia , Obuekwe Chike 
Published: May 2021

AbstractThis paper aims to explore and understand the digital divide in older adults when accepting and using smart devices within an organization. Using an in-depth single case study, the digital divide is explored and understood using technology-mediated learning for older adults when using smart devices; ie. tablet devices. The case study is based on a group of educated, older Indian adult volunteers at a local Punjabi radio station. A qualitative approach used the data collection techniques of interviews, observations, informal conversations and reference to archival documents and interpretivism for analysis. Our findings revealed that older adults with ailments have shorter lives, contrary to popular perception, can be very active in their communities, are able to use basic IT and are willing to use technology when it leads to significant tangible or intangible benefits without considering the remaining time of their lives. Contributions for policymakers and industry are also offered in this paper.
Crossing the Maelstrom: New Departures in Viking Archaeology
Authors: Lund Julie , Sindbæk Søren M. 
Published: May 2021

AbstractThis paper reviews the achievements and challenges of archaeological research on Viking Age northern Europe and explores potential avenues for future research. We identify the reemergence of comparative and cross-cultural perspectives along with a turn toward studying mobility and maritime expansion, fueled by the introduction of biomolecular and isotopic data. The study of identity has seen a shift from a focus on collective beliefs and ritual to issues of personal identity and presentation, with a corresponding shift in attention to individual burials and the “animated objects.” Network ontologies have brought new perspectives on the emergence of sea trade and urban nodes and to the significance of outfield production and resources. Field archaeology has seen an emphasis on elite manors, feasting halls, and monuments, as well as military sites andthingassembly places, using new data from remote sensing, geophysical surveys, geoarchaeology, and metal detectors. Concerns over current climate change have placed the study of environment as a key priority, in particular in the ecologically vulnerable North Atlantic settlements. Discussing future directions, we call for alignment between societal/economic and individual/cultural perspectives, and for more ethically grounded research. We point to diaspora theory and intersectionality as frameworks with the potential to integrate genomics, identity, and society, and to ecology as a framework for integrating landscape, mobility, and political power.
Licensing imperative subjects without an imperative operator
Authors: van Alem Astrid 
Published: May 2021

AbstractIt is often assumed that imperatives contain a covert imperative licenser, such as an imperative operator. The purpose of the operator is to bind the imperative subject, and thereby derive a number of the syntactic properties of imperatives. In this paper, I show, based on variation in V2 imperatives in varieties of Dutch and German, that if there is an alternative way of licensing the imperative subject, presence of an imperative operator is not necessary. I put forth the novel observation that V2 imperatives are only allowed in varieties that have verbal umlaut. I argue that verbal umlaut corresponds to a syntactic encoding of person features on the imperative verb, which can bind the imperative subject. This voids the need for an imperative operator in SpecCP, and gives way to V2 imperatives in V2 languages like Dutch and German. The implication is that a covert imperative licenser is a last resort mechanism, rather than an inherent part of imperatives clauses.
Review of image segmentation techniques for layup defect detection in the Automated Fiber Placement process
Authors: Meister Sebastian , Wermes Mahdieu A. M. , Stüve Jan , Groves Roger M. 
Published: May 2021

AbstractThe aerospace industry has established the Automated Fiber Placement process as a common technique for manufacturing fibre reinforced components. In this process multiple composite tows are placed simultaneously onto a tool. Currently in such processes manual testing requires often up to 50% of the manufacturing duration. Moreover, the accuracy of quality assurance varies significantly with the inspector in charge. Thus, inspection automation provides an effective way to increase efficiency. However, to achieve a proper inspection performance, the segmentation of layup defects need to be examined. In order to improve such defect detection systems, this paper performs a comprehensive ranking of segmentation techniques. Thus, 29 statistical, spectral and structural algorithms from related work were evaluated based on nine substantial criteria as assessed from literature and process requirements. For reasons of determinism and easy technology transferability without the need of much training data, the development of new Machine Learning algorithms is not part of this paper. Afterwards, seven of the most auspicious algorithms were studied experimentally. Therefore, laser line scan sensor depth maps from fibre placement defects were utilised. Furthermore noisy images were generated and applied for testing algorithm robustness. The test data contained five defect categories with 50 samples per class. It was concluded that Adaptive Thresholding and Cell Wise Standard Deviation Thresholding work best yielding detection accuracies mostly $$> 97$$

>
97

%. Noteworthy is that influenced input data can affect the detection results. Feasible algorithms with sensible parameter settings were able to perform reliable defect segmentation for layed material.
Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features
Authors: Juppet Quentin , De Martino Fabio , Marcandalli Elodie , Weigert Martin , Burri Olivier , Unser Michael , Brisken Cathrin , Sage Daniel 
Published: May 2021

AbstractPatient-Derived Xenografts (PDXs) are the preclinical models which best recapitulate inter- and intra-patient complexity of human breast malignancies, and are also emerging as useful tools to study the normal breast epithelium. However, data analysis generated with such models is often confounded by the presence of host cells and can give rise to data misinterpretation. For instance, it is important to discriminate between xenografted and host cells in histological sections prior to performing immunostainings. We developed Single Cell Classifier (SCC), a data-driven deep learning-based computational tool that provides an innovative approach for automated cell species discrimination based on a multi-step process entailing nuclei segmentation and single cell classification. We show that human and murine cell contextual features, more than cell-intrinsic ones, can be exploited to discriminate between cell species in both normal and malignant tissues, yielding up to 96% classification accuracy. SCC will facilitate the interpretation of H&E- and DAPI-stained histological sections of xenografted human-in-mouse tissues and it is open to new in-house built models for further applications. SCC is released as an open-source plugin in ImageJ/Fiji available at the following link: https://github.com/Biomedical-Imaging-Group/SingleCellClassifier.
A machine learning based sentient multimedia framework to increase safety at work
Authors: Bonifazi Gianluca , Corradini Enrico , Ursino Domenico , Virgili Luca , Anceschi Emiliano , De Donato Massimo Callisto 
Published: May 2021

AbstractIn the last few decades, we have witnessed an increasing focus on safety in the workplace. ICT has always played a leading role in this context. One ICT sector that is increasingly important in ensuring safety at work is the Internet of Things and, in particular, the new architectures referring to it, such as SIoT, MIoT and Sentient Multimedia Systems. All these architectures handle huge amounts of data to extract predictive and prescriptive information. For this purpose, they often make use of Machine Learning. In this paper, we propose a framework that uses both Sentient Multimedia Systems and Machine Learning to support safety in the workplace. After the general presentation of the framework, we describe its specialization to a particular case, i.e., fall detection. As for this application scenario, we describe a Machine Learning based wearable device for fall detection that we designed, built and tested. Moreover, we illustrate a safety coordination platform for monitoring the work environment, activating alarms in case of falls, and sending appropriate advices to help workers involved in falls.
Geometric analysis of mixed-mode oscillations in a model of electrical activity in human beta-cells
Authors: Battaglin Simone , Pedersen Morten Gram 
Published: May 2021

AbstractHuman pancreatic beta-cells may exhibit complex mixed-mode oscillatory electrical activity, which underlies insulin secretion. A recent biophysical model of human beta-cell electrophysiology can simulate such bursting behavior, but a mathematical understanding of the model’s dynamics is still lacking. Here we exploit time-scale separation to simplify the original model to a simpler three-dimensional model that retains the behavior of the original model and allows us to apply geometric singular perturbation theory to investigate the origin of mixed-mode oscillations. Changing a parameter modeling the maximal conductance of a potassium current, we find that the reduced model possesses a singular Hopf bifurcation that results in small-amplitude oscillations, which go through a period-doubling sequence and chaos until the birth of a large-scale return mechanism and bursting dynamics. The theory of folded node singularities provide insight into the bursting dynamics further away from the singular Hopf bifurcation and the eventual transition to simple spiking activity. Numerical simulations confirm that the insight obtained from the analysis of the reduced model can be lifted back to the original model.
A Maize (Zea mays L.) BIK1-Like Receptor-Like Cytoplasmic Kinase Contributes to Disease Resistance
Authors: Li Weiran , Liao Chao-Jan , Bluhm Burt H. , Mengiste Tesfaye , Woloshuk Charles P. 
Published: May 2021

AbstractReceptor-like cytoplasmic kinases (RLCKs) form a large subfamily of proteins in plants. RLCKs are known to regulate plant immunity to bacterial and fungal pathogens. In this study, we analyzed the genome-wide complement of maize RLCK genes and conducted detailed studies on one maize RLCK. The maize genome encodes 192 RLCKs that largely mirror the RLCK family in other plants. Previous studies implicated Arabidopsis BOTRYTIS INDUCED KINASE1 (BIK1) and TOMATO PROTEIN KINASE 1b (TPK1b) in plant resistance to the bacterial pathogen Pseudomonas syringae and the fungal pathogen Botrytis cinerea. A novel maize RLCK, Zea Mays BIK1-LIKE KINASE 1 (ZmBLK1), was identified based on sequence similarity to the tomato and Arabidopsis RLCKs. We demonstrated that ZmBLK1 displays protein kinase activity in vitro and the protein localizes to the plasma membrane. Importantly, expression of ZmBLK1 partially rescued the growth and disease phenotypes of the Arabidopsis bik1 mutant plants. The expression of ZmBLK1 was induced in maize at 12 h after inoculation with Clavibacter michiganensis subsp. nebraskensis (CMN), the bacterial pathogen causing Goss’s wilt. Interestingly, overexpression of ZmBLK1 in transgenic maize increased resistance to CMN but did not impact resistance to Aspergillus ear rot caused by the fungal pathogen Aspergillus flavus and the associated aflatoxin contamination. These findings support our hypothesis that ZmBLK1 contributes to plant resistance to bacterial pathogens likely by modulating events early after pathogen infection, implying that the protein may interact with other membrane proteins early in the immune response pathway.
Inequalities between overpartition ranks for all moduli
Authors: Ciolan Alexandru 
Published: May 2021

AbstractIn this paper we give a full description of the inequalities that can occur between overpartition ranks modulo $$ c\ge 2. $$

c
≥
2
.

If $$ \overline{N}(a,c,n) $$

N
¯

(
a
,
c
,
n
)

denotes the number of overpartitions of n with rank congruent to a modulo c, we prove that for any $$ c\ge 7 $$

c
≥
7

and $$ 0\le a<b\le \left\lfloor \frac{c}{2}\right\rfloor $$

0
≤
a
<
b
≤

c
2

we have $$ \overline{N}(a,c,n)>\overline{N}(b,c,n) $$

N
¯

(
a
,
c
,
n
)

>

N
¯

(
b
,
c
,
n
)

for n large enough. That the sign of the rank differences $$ \overline{N}(a,c,n)-\overline{N}(b,c,n) $$

N
¯

(
a
,
c
,
n
)

-

N
¯

(
b
,
c
,
n
)

depends on the residue class of n modulo c in the case of small moduli, such as $$ c=6, $$

c
=
6
,

is known due to the work of Ji et al. (J Number Theory 184:235–269, 2018) and Ciolan (Int J Number Theory 16(1):121–143, 2020). We show that the same behavior holds for $$ c\in \{2,3, 4,5\}. $$

c
∈
{
2
,
3
,
4
,
5
}
.
Topic space trajectories
Authors: Schaefermeier Bastian , Stumme Gerd , Hanika Tom 
Published: May 2021

AbstractThe annual number of publications at scientific venues, for example, conferences and journals, is growing quickly. Hence, even for researchers it becomes harder and harder to keep track of research topics and their progress. In this task, researchers can be supported by automated publication analysis. Yet, many such methods result in uninterpretable, purely numerical representations. As an attempt to support human analysts, we present topic space trajectories, a structure that allows for the comprehensible tracking of research topics. We demonstrate how these trajectories can be interpreted based on eight different analysis approaches. To obtain comprehensible results, we employ non-negative matrix factorization as well as suitable visualization techniques. We show the applicability of our approach on a publication corpus spanning 50 years of machine learning research from 32 publication venues. In addition to a thorough introduction of our method, our focus is on an extensive analysis of the results we achieved. Our novel analysis method may be employed for paper classification, for the prediction of future research topics, and for the recommendation of fitting conferences and journals for submitting unpublished work. An advantage in these applications over previous methods lies in the good interpretability of the results obtained through our methods.