bluuebunny/crossref_metadata_2025_split huggingface dataset:
SaS-BCI: a new strategy to predict image memorability and use mental imagery as a brain-based biometric authentication
Authors: Yousefi Fares , Kolivand Hoshang , Baker Thar 
Published: August 2020

AbstractSecurity authentication is one of the most important levels of information security. Nowadays, human biometric techniques are the most secure methods for authentication purposes that cover the problems of older types of authentication like passwords and pins. There are many advantages of recent biometrics in terms of security; however, they still have some disadvantages. Progresses in technology made some specific devices, which make it possible to copy and make a fake human biometric because they are all visible and touchable. According to this matter, there is a need for a new biometric to cover the issues of other types. Brainwave is human data, which uses them as a new type of security authentication that has engaged many researchers. There are some research and experiments, which are investigating and testing EEG signals to find the uniqueness of human brainwave. Some researchers achieved high accuracy rates in this area by applying different signal acquisition techniques, feature extraction and classifications using Brain–Computer Interface (BCI). One of the important parts of any BCI processes is the way that brainwaves could be acquired and recorded. A new Signal Acquisition Strategy is presented in this paper for the process of authorization and authentication of brain signals specifically. This is to predict image memorability from the user’s brain to use mental imagery as a visualization pattern for security authentication. Therefore, users can authenticate themselves with visualizing a specific picture in their minds. In conclusion, we can see that brainwaves can be different according to the mental tasks, which it would make it harder using them for authentication process. There are many signal acquisition strategies and signal processing for brain-based authentication that by using the right methods, a higher level of accuracy rate could be achieved which is suitable for using brain signal as another biometric security authentication.
Rigidity for perimeter inequality under spherical symmetrisation
Authors: Cagnetti F. , Perugini M. , Stöger D. 
Published: August 2020

AbstractNecessary and sufficient conditions for rigidity of the perimeter inequality under spherical symmetrisation are given. That is, a characterisation for the uniqueness (up to orthogonal transformations) of the extremals is provided. This is obtained through a careful analysis of the equality cases, and studying fine properties of the circular symmetrisation, which was firstly introduced by Pólya in 1950.
Concentration Fluctuations from Localized Atmospheric Releases
Authors: Cassiani Massimo , Bertagni Matteo B. , Marro Massimo , Salizzoni Pietro 
Published: August 2020

AbstractWe review the efforts made by the scientific community in more than seventy years to elucidate the behaviour of concentration fluctuations arising from localized atmospheric releases of dynamically passive and non-reactive scalars. Concentration fluctuations are relevant in many fields including the evaluation of toxicity, flammability, and odour nuisance. Characterizing concentration fluctuations requires not just the mean concentration but also at least the variance of the concentration in the location of interest. However, for most purposes the characterization of the concentration fluctuations requires knowledge of the concentration probability density function (PDF) in the point of interest and even the time evolution of the concentration. We firstly review the experimental works made both in the field and in the laboratory, and cover both point sources and line sources. Regarding modelling approaches, we cover analytical, semi-analytical, and numerical methods. For clarity of presentation we subdivide the models in two groups, models linked to a transport equation, which usually require a numerical resolution, and models mainly based on phenomenological aspects of dispersion, often providing analytical or semi-analytical relations. The former group includes: large-eddy simulations, Reynolds-averaged Navier–Stokes methods, two-particle Lagrangian stochastic models, PDF transport equation methods, and heuristic Lagrangian single-particle methods. The latter group includes: fluctuating plume models, semi-empirical models for the concentration moments, analytical models for the concentration PDF, and concentration time-series models. We close the review with a brief discussion highlighting possible useful additions to experiments and improvements to models.
Potential for Sustainable Aquaculture: Insights from Discrete Choice Experiments
Authors: Xuan Bui Bich , Sandorf Erlend Dancke 
Published: August 2020

AbstractThe growth in global aquaculture production may address the lack of sustainability in wild fisheries, alleviate poverty in rural and coastal areas, and help meet the worldwide increase in demand for animal protein. However, there is an ongoing debate about the severity of the environmental impact of aquaculture production. Investing in new high-tech production systems can address both productivity growth and the environmental externalities, but high investment costs hinder adoption of high-tech production methods. We investigate the potential of a payment for environmental services program easing access to capital for producers to increase willingness-to-invest in more sustainable aquaculture practices in Vietnam. We conducted two discrete choice experiments to explore the supply and demand side of the policy. First, we elicited the public’s willingness-to-pay to reduce the environmental impact of conventional shrimp aquaculture, and second, we elicited farmers willingness-to-accept a credit subsidy to invest in high-tech production methods. Our results show that the public care about reduced environmental impacts, while farmers strongly prefer increased productivity. Furthermore, the public’s willingness-to-pay for reduced environmental impacts exceeds producer’s willingness-to-accept a subsidy to invest under most scenarios. This implies a potential for more sustainable aquaculture production in Vietnam.
Wait for it: identifying “On-Hold” self-admitted technical debt
Authors: Maipradit Rungroj , Treude Christoph , Hata Hideaki , Matsumoto Kenichi 
Published: August 2020

AbstractSelf-admitted technical debt refers to situations where a software developer knows that their current implementation is not optimal and indicates this using a source code comment. In this work, we hypothesize that it is possible to develop automated techniques to understand a subset of these comments in more detail, and to propose tool support that can help developers manage self-admitted technical debt more effectively. Based on a qualitative study of 333 comments indicating self-admitted technical debt, we first identify one particular class of debt amenable to automated management: on-hold self-admitted technical debt (on-hold SATD), i.e., debt which contains a condition to indicate that a developer is waiting for a certain event or an updated functionality having been implemented elsewhere. We then design and evaluate an automated classifier which can identify these on-hold instances with an area under the receiver operating characteristic curve (AUC) of 0.98 as well as detect the specific conditions that developers are waiting for. Our work presents a first step towards automated tool support that is able to indicate when certain instances of self-admitted technical debt are ready to be addressed.
The affective assemblage of internationalisation in Japanese higher education
Authors: Morley Louise , Roberts Paul , Ota Hiroshi 
Published: August 2020

AbstractPositive attributes stick to higher education internationalisation, and it is a policy paradigm with performative effects. Internationalisation draws on imagined virtuous flows of knowledge production and exchange, and is presented as an assemblage of detraditionalisation, expansiveness and epistemic and cultural opportunity for individuals, organisations and nation states. Policies target bodies, minds and affect, yet are presented as an unquestionable good in an imagined genderneutral, borderless, meritocratic and benign global knowledge economy. This paper explores the affective economy of internationalisation drawing upon interview data gathered in fifteen private, five national and eight public universities in Japan with thirty-four migrant academics and thirteen international doctoral researchers. We aim to contribute to internationalisation theory by exploring the sticky micropolitics of internationalisation in relation to affective assemblages, and how the gendered, racialised, linguistic and epistemic inequalities constituting academic mobility are frequently disqualified from discourse. Our discussion includes consideration of the Japanese policy context, the concept of affective assemblages, navigating gender regimes, precarity and linguistic imperialism. We conclude that the immaterial or affective labour that is required to unstick, install and maintain an internationalised academic identity and navigate the translations and antagonisms from everyday encounters with difference is substantially under-estimated.
Estimation of pulse pressure variation and cardiac output in patients having major abdominal surgery: a comparison between a mobile application for snapshot pulse wave analysis and invasive pulse wave analysis
Authors: Hoppe Phillip , Gleibs Fabian , Briesenick Luisa , Joosten Alexandre , Saugel Bernd 
Published: August 2020

AbstractPulse pressure variation (PPV) and cardiac output (CO) can guide perioperative fluid management. Capstesia (Galenic App, Vitoria-Gasteiz, Spain) is a mobile application for snapshot pulse wave analysis (PWAsnap) and estimates PPV and CO using pulse wave analysis of a snapshot of the arterial blood pressure waveform displayed on any patient monitor. We evaluated the PPV and CO measurement performance of PWAsnap in adults having major abdominal surgery. In a prospective study, we simultaneously measured PPV and CO using PWAsnap installed on a tablet computer (PPVPWAsnap, COPWAsnap) and using invasive internally calibrated pulse wave analysis (ProAQT; Pulsion Medical Systems, Feldkirchen, Germany; PPVProAQT, COProAQT). We determined the diagnostic accuracy of PPVPWAsnap in comparison to PPVProAQT according to three predefined PPV categories and by computing Cohen’s kappa coefficient. We compared COProAQT and COPWAsnap using Bland-Altman analysis, the percentage error, and four quadrant plot/concordance rate analysis to determine trending ability. We analyzed 190 paired PPV and CO measurements from 38 patients. The overall diagnostic agreement between PPVPWAsnap and PPVProAQT across the three predefined PPV categories was 64.7% with a Cohen’s kappa coefficient of 0.45. The mean (± standard deviation) of the differences between COPWAsnap and COProAQT was 0.6 ± 1.3 L min− 1 (95% limits of agreement 3.1 to − 1.9 L min− 1) with a percentage error of 48.7% and a concordance rate of 45.1%. In adults having major abdominal surgery, PPVPWAsnap moderately agrees with PPVProAQT. The absolute and trending agreement between COPWAsnap with COProAQT is poor. Technical improvements are needed before PWAsnap can be recommended for hemodynamic monitoring.
Determinants of Women’s Drug Use During Pregnancy: Perspectives from a Qualitative Study
Authors: Mburu Gitau , Ayon Sylvia , Mahinda Samantha , Kaveh Khoshnood 
Published: August 2020

AbstractIntroductionDrug use during pregnancy can have negative effects on maternal and child health. However, there is a dearth of data regarding drug use among pregnant women in Kenya, where illicit drug use is on the rise. In this paper, we report factors influencing women’s decisions to use drugs during pregnancy.MethodsIn 2015, we conducted in-depth interviews and focus group discussions with 45 women who inject drugs and five key stakeholders involved in provision of services to people who use drugs in coastal Kenya. Inductive thematic analysis was conducted to draw out themes related to key determinants of drug use during pregnancy.ResultsFour key themes emerged outlining determinants of drug use during pregnancy: (i) the use of drugs to cope with the stress of unexpected pregnancy, (ii) the continued drug use during pregnancy to manage withdrawal, (iii) the dual effect of pregnancy on drug use either as a facilitator or as a moderator of drug use, and (iv) the role of male intimate partner in influencing women’s drug use during pregnancy.ConclusionOur paper reports women’s drug use during pregnancy and the factors influencing this phenomenon. To safeguard the health and well-being of pregnant women and their unborn children, there is a need for education and awareness raising, implementing couple-based harm reduction approaches to leverage on positive male influences, improving availability of drug treatment, and provision of family planning interventions for women who use drugs.
The Guidance Theory of Action: A Critical Review
Authors: Asma Lieke Joske Franci 
Published: August 2020

AbstractTheories based on Frankfurt’s (Am Philos Q 15(2):157–162, 1978) view of action have recently been developed to account for passive, automatic, and habitual actions. What these theories share is that they aim to distinguish between actions and mere bodily movements without appealing to psychological states as causes. Instead, agents have guidance control over their actions. In this paper I argue that the versions of the theory that have been proposed are problematic. I propose to pay attention to Frankfurt’s other claim instead: that actions and mere bodily movements are inherently different. I argue that Anscombe’s approach to action does take this inherent distinction seriously, and is able to account for passive, automatic, and habitual actions.
Computational Goals, Values and Decision-Making
Authors: Dennis Louise A. 
Published: August 2020

AbstractConsidering the popular framing of an artificial intelligence as a rational agent that always seeks to maximise its expected utility, referred to as its goal, one of the features attributed to such rational agents is that they will never select an action which will change their goal. Therefore, if such an agent is to be friendly towards humanity, one argument goes, we must understand how to specify this friendliness in terms of a utility function. Wolfhart Totschnig (Fully Autonomous AI, Science and Engineering Ethics, 2020), argues in contrast that a fully autonomous agent will have the ability to change its utility function and will do so guided by its values. This commentary examines computational accounts of goals, values and decision-making. It rejects the idea that a rational agent will never select an action that changes its goal but also argues that an artificial intelligence is unlikely to be purely rational in terms of always acting to maximise a utility function. It nevertheless also challenges the idea that an agent which does not change its goal cannot be considered fully autonomous. It does agree that values are an important component of decision-making and explores a number of reasons why.
Optimum tubing size prediction model for vertical multiphase flow during flow production period of oil wells
Authors: Nwanwe C. C. , Duru U. I. , Nwanwe O. I. , Chikwe A. O. , Ojiabo K. T. , Umeojiakor C. T. 
Published: August 2020

AbstractOptimum tubing size (OTS) selection was traditionally done by using nodal analysis to perform sensitivity analysis on the different tubing sizes. This approach was found to be both cumbersome and time-consuming. This study developed a user-friendly and time-efficient OTS prediction computer model that could allow Petroleum Production Engineers to select the best tubing size for any vertical oil well. The tubing size selection was based on the present operating flow rate, economic considerations and future operating flow rate as defined by the OTS selection criteria of this study. The robustness of the model was tested using tubing sizes ranging from 0.824 to 6.0 inch in a vertical well producing from both saturated and undersaturated oil reservoirs. The 2.750-inch tubing was found the OTS for both scenarios. In the validation, the results obtained from the novel OTS prediction model and Guo et al. (Petroleum production engineering: a computer-assisted approach, Gulf Professional Publishing, Cambridge) spreadsheet program using the Poetmann–Carpenter method were in excellent agreement for operating flow rate but not for operating pressure. Furthermore, the novel OTS prediction model was in excellent agreement with the same spreadsheet program based on modified Hagedorn–Brown correlation for both operating flow rate and pressure. The results showed that the model developed in this study is reliable and can be used in the field for vertical oil wells. The new model could as well inform the Production Engineer when the well would need artificial lift for economic production of the well. It was recommended that Newton–Raphson and modified Hagedorn–Brown methods be used in future study.
Novel and potent inhibitors targeting DHODH are broad-spectrum antivirals against RNA viruses including newly-emerged coronavirus SARS-CoV-2
Authors: Xiong Rui , Zhang Leike , Li Shiliang , Sun Yuan , Ding Minyi , Wang Yong , Zhao Yongliang , Wu Yan , Shang Weijuan , Jiang Xiaming , Shan Jiwei , Shen Zihao , Tong Yi , Xu Liuxin , Chen Yu , Liu Yingle , Zou Gang , Lavillete Dimitri , Zhao Zhenjiang , Wang Rui , Zhu Lili , Xiao Gengfu , Lan Ke , Li Honglin , Xu Ke 
Published: August 2020

AbstractEmerging and re-emerging RNA viruses occasionally cause epidemics and pandemics worldwide, such as the on-going outbreak of the novel coronavirus SARS-CoV-2. Herein, we identified two potent inhibitors of human DHODH, S312 and S416, with favorable drug-likeness and pharmacokinetic profiles, which all showed broad-spectrum antiviral effects against various RNA viruses, including influenza A virus, Zika virus, Ebola virus, and particularly against SARS-CoV-2. Notably, S416 is reported to be the most potent inhibitor so far with an EC50 of 17 nmol/L and an SI value of 10,505.88 in infected cells. Our results are the first to validate that DHODH is an attractive host target through high antiviral efficacy in vivo and low virus replication in DHODH knock-out cells. This work demonstrates that both S312/S416 and old drugs (Leflunomide/Teriflunomide) with dual actions of antiviral and immuno-regulation may have clinical potentials to cure SARS-CoV-2 or other RNA viruses circulating worldwide, no matter such viruses are mutated or not.
Prädiktoren von Sturzereignissen in Pflegewohnheimen: eine Querschnittsstudie in Deutschland
Authors: Strutz Nicole , Kiselev Jörn , Lahmann Nils 
Published: August 2020

Zusammenfassung
Hintergrund
Neuere Studienergebnisse zeigen, dass Sturzereignisse in Pflegewohnheimen bisher nicht in ausreichendem Maße verhindert werden können. Der Zusammenhang zwischen Sturzereignissen sowie Mobilitätseinschränkungen, Erkrankungen und Body-Mass-Index (BMI) wurde für jeden Faktor bisher einzeln beschrieben; eine komplexere Analyse fehlt.

Ziel
Ziel dieser Studie ist es, neben der Sturzinzidenz, Sturzprädiktoren in deutschen Pflegewohnheimen zu ermitteln. Die Untersuchung fokussiert auf das Vorliegen möglicher Sturzprädiktoren von Pflegeheimbewohnern/Pflegeheimbewohnerinnen ab 65 Jahren und versucht, evtl. vorhandene, besonders vulnerable Personengruppen zu identifizieren.

Material und Methode
Querschnittserhebung mit 2427 Pflegeheimbewohnern/Pflegeheimbewohnerinnen im 3. und 4. Lebensalter aus 17 deutschen Pflegewohnheimen im Untersuchungszeitraum von 2014 bis 2016. Es wurden umfangreiche Daten zur Mobilität, zu Erkrankungen und BMI sowie zur Versorgung mit Mobilitätshilfsmitteln erhoben und statistisch ausgewertet. Zur Ermittlung multivariater Zusammenhänge wurde ein „classification and regression tree“ angewendet.

Ergebnisse
Die Gruppe der Proband*innen stellt sich mit einem Median von 85 Jahren und einem Frauenanteil von 73,8 % dar. Im Erhebungszeitraum von 2014 bis 2016 stürzten 5,5 % der Pflegeheimbewohner*innen. Als mögliche Prädiktoren für Sturzereignisse konnten Einschränkungen in mehreren spezifischen komplexen Bewegungsabläufen sowie ein geringer BMI ≤21,5 kg/m2 ermittelt werden. Die Gruppe der Pflegeheimbewohner*innen mit geringem BMI zeigt Einschränkungen in anderen Bewegungsabläufen als Pflegeheimbewohner*innen der Gruppe, die einen BMI >21,5 kg/m2 aufweisen. Pflegeheimbewohner*innen mit diesen Merkmalen wurden als besonders vulnerable Gruppen identifiziert.

Schlussfolgerung
Da die Einschätzung des Sturzrisikos von Pflegeheimbewohnern/Pflegeheimbewohnerinnen auf Basis bisheriger Risikofaktoren nur teilweise erfolgreich erfolgt, scheint die Anwendung geeigneter Testverfahren zur Bestimmung der Mobilität und des BMI angezeigt, um das Sturzrisiko von Pflegeheimbewohnern/Pflegeheimbewohnerinnen belastbar bestimmen und geeignete Maßnahmen ergreifen zu können.
All modular forms of weight 2 can be expressed by Eisenstein series
Authors: Raum Martin , Xia Jiacheng 
Published: August 2020

AbstractWe show that every elliptic modular form of integral weight greater than 1 can be expressed as linear combinations of products of at most two cusp expansions of Eisenstein series. This removes the obstruction of nonvanishing central $$\mathrm{L}$$
L
-values present in all previous work. For weights greater than 2, we refine our result further, showing that linear combinations of products of exactly two cusp expansions of Eisenstein series suffice.
Framework for role discovery using transfer learning
Authors: Kikuta Shumpei , Toriumi Fujio , Nishiguchi Mao , Liu Shu , Fukuma Tomoki , Nishida Takanori , Usui Shohei 
Published: August 2020

AbstractDiscovering the node roles in a network helps to solve diverse social problems. Role discovery attempts to predict the node roles from a network structure, and this method has been extensively studied in various fields. Role discovery using transfer learning has many advantages, but methods using this approach face two kinds of problems: domain-shift problems and model selection. To address these problems, we propose a general framework that includes network representation learning, domain adversarial learning for suppressing domain-shift problems, and model selection without using target labels. As a result of computational experiments, we show on publicly available datasets that the proposed model outperforms conventional methods, the proposed model selection method performs well without using target labels, and the proposed method can be used in real-world datasets. Furthermore, we found that our framework suppressed domain-shift problems, worked well even with differences between networks, and could handle imbalanced classes.