bluuebunny/crossref_metadata_2025_split huggingface dataset:
variED: an editor for collaborative, real-time feature modeling
Authors: Kuiter Elias , Krieter Sebastian , Krüger Jacob , Saake Gunter , Leich Thomas 
Published: March 2021

AbstractFeature models are a helpful means to document, manage, maintain, and configure the variability of a software system, and thus are a core artifact in software product-line engineering. Due to the various purposes of feature models, they can be a cross-cutting concern in an organization, integrating technical and business aspects. For this reason, various stakeholders (e.g., developers and consultants) may get involved into modeling the features of a software product line. Currently, collaboration in such a scenario can only be done with face-to-face meetings or by combining single-user feature-model editors with additional communication and version-control systems. While face-to-face meetings are often costly and impractical, using version-control systems can cause merge conflicts and inconsistency within a model, due to the different intentions of the involved stakeholders. Advanced tools that solve these problems by enabling collaborative, real-time feature modeling, analogous to Google Docs or Overleaf for text editing, are missing. In this article, we build on a previous paper and describe (1) the extended formal foundations of collaborative, real-time feature modeling, (2) our conflict resolution algorithm in more detail, (3) proofs that our formalization converges and preserves causality as well as user intentions, (4) the implementation of our prototype, and (5) the results of an empirical evaluation to assess the prototype’s usability. Our contributions provide the basis for advancing existing feature-modeling tools and practices to support collaborative feature modeling. The results of our evaluation show that our prototype is considered helpful and valuable by 17 users, also indicating potential for extending our tool and opportunities for new research directions.
A validated model for the scoping process of quality requirements: a multi-case study
Authors: Olsson Thomas , Wnuk Krzysztof , Jansen Slinger 
Published: March 2021

AbstractQuality requirements are vital to developing successful software products. However, there exist evidence that quality requirements are managed mostly in an “ad hoc” manner and down-prioritized. This may result in insecure, unstable, slow products, and unhappy customers. We have developed a conceptual model for the scoping process of quality requirements – QREME – and an assessment model – Q-REPM – for companies to benchmark when evaluating and improving their quality requirements practices. Our model balances an upfront forward-loop with a data-driven feedback-loop. Furthermore, it addresses both strategic and operational decisions. We have evaluated the model in a multi-case study at two companies in Sweden and three companies in The Netherlands. We assessed the scoping process practices for quality requirements and provided improvement recommendations for which practices to improve. The study confirms the existence of the constructs underlying QREME. The companies perform, in the median, 24% of the suggested actions in Q-REPM. None of the companies work data-driven with their quality requirements, even though four out of five companies could technically do so. Furthermore, on the strategic level, quality requirements practices are not systematically performed by any of the companies. The conceptual model and assessment model capture a relevant view of the quality requirements practices and offer relevant improvement proposals. However, we believe there is a need for coupling quality requirements practices to internal and external success factors to motive companies to change their ways of working. We also see improvement potential in the area of business intelligence for QREME in selecting data sources and relevant stakeholders.
TPOT-NN: augmenting tree-based automated machine learning with neural network estimators
Authors: Romano Joseph D. , Le Trang T. , Fu Weixuan , Moore Jason H. 
Published: March 2021

AbstractAutomated machine learning (AutoML) and artificial neural networks (ANNs) have revolutionized the field of artificial intelligence by yielding incredibly high-performing models to solve a myriad of inductive learning tasks. In spite of their successes, little guidance exists on when to use one versus the other. Furthermore, relatively few tools exist that allow the integration of both AutoML and ANNs in the same analysis to yield results combining both of their strengths. Here, we present TPOT-NN—a new extension to the tree-based AutoML software TPOT—and use it to explore the behavior of automated machine learning augmented with neural network estimators (AutoML+NN), particularly when compared to non-NN AutoML in the context of simple binary classification on a number of public benchmark datasets. Our observations suggest that TPOT-NN is an effective tool that achieves greater classification accuracy than standard tree-based AutoML on some datasets, with no loss in accuracy on others. We also provide preliminary guidelines for performing AutoML+NN analyses, and recommend possible future directions for AutoML+NN methods research, especially in the context of TPOT.
Teaching digital models: secondary technology teachers’ experiences
Authors: Brink Helen , Kilbrink Nina , Gericke Niklas 
Published: March 2021

AbstractIn secondary technology education, models of artifacts, systems and processes, visualized and simulated through digital tools (digital models) are a relatively new element. Technology teachers teach digital models to meet syllabus criteria of digital competence, applicable to for instance problem solving and documentation using digital tools. However, there is a lack of knowledge concerning how teachers use digital models in their teaching, what their intentions are, and what content they choose. It is known, though, that teachers’ experiences influence the teaching. Therefore, the aim of this study is to investigate teachers’ experiences of teaching digital models in compulsory school, to contribute to more knowledge of teaching in this area. This study takes a phenomenological lifeworld approach, and 12 semi-structured interviews with lower secondary technology teachers form the empirical data. The data were analyzed thematically and the results are four themes of experiencing the teaching of digital models, indicating that technology teachers teach with different aims and purposes; Enhancing and integrating other subjects, Visualizing technology to the pupils, Enabling digital modelling, and Preparing pupils for the future. Further, the results also indicate that the content and methods of teaching differ and that teachers did not experience digital models as one single idea but as an amalgam of multiple ideas. These findings can be used as a basis for further research and development of teaching concerning digital models.
Some Remarks on Replicated Simulated Annealing
Authors: Gripon Vicent , Löwe Matthias , Vermet Franck 
Published: March 2021

AbstractRecently authors have introduced the idea of training discrete weights neural networks using a mix between classical simulated annealing and a replica ansatz known from the statistical physics literature. Among other points, they claim their method is able to find robust configurations. In this paper, we analyze this so called “replicated simulated annealing” algorithm. In particular, we give criteria to guarantee its convergence, and study when it successfully samples from configurations. We also perform experiments using synthetic and real data bases.
Soft biometrics: a survey
Authors: Hassan Bilal , Izquierdo Ebroul , Piatrik Tomas 
Published: March 2021

AbstractThe field of biometrics research encompasses the need to associate an identity to an individual based on the persons physiological or behaviour traits. While the use of intrusive techniques such as retina scans and finger print identification has resulted in highly accurate systems, the scalability of such systems in real-world applications such as surveillance and border security has been limited. As a branch of biometrics research, the origin of soft biometrics could be traced back to need for non-intrusive solutions for extracting physiological traits of a person. Following high number of research outcomes reported in the literature on soft biometrics, this paper aims to consolidate the scope of soft biometrics research across four thematic schemes (i) a detailed review of soft biometrics research data sets, their annotation strategies and building a largest novel collection of soft traits; (ii) the assessment of metrics that affect the performance of soft biometrics system; (iii) a comparative analysis on feature and modality level fusion reported in the literature for enhancing the system performance; and (iv) a performance analysis of hybrid soft biometrics recognition system using multi-scale criterion. The paper also presents a detailed analysis on the global traits associated to person identity such as gender, age and ethnicity. The contribution of the paper is to provide a comprehensive review of scientific literature, identify open challenges and offer insights on new research directions in the filed.
Fractional-order single state reset element
Authors: Karbasizadeh Nima , Saikumar Niranjan , HosseinNia S. Hassan 
Published: March 2021

AbstractThis paper proposes a fractional-order reset element whose architecture allows for the suppression of nonlinear effects for a range of frequencies. Suppressing the nonlinear effects of a reset element for the desired frequency range while maintaining it for the rest is beneficial, especially when it is used in the framework of a “Constant in gain, Lead in phase” (CgLp) filter. CgLp is a newly introduced nonlinear filter, bound to circumvent the well-known linear control limitation—the waterbed effect. The ideal behaviour of such a filter in the frequency domain is unity gain while providing a phase lead for a broad range of frequencies. However, CgLp’s ideal behaviour is based on the describing function, which is a first-order approximation that neglects the effects of the higher-order harmonics in the output of the filter. Although CgLp is fundamentally a nonlinear filter, its nonlinearity is not required for all frequencies. Thus, it is shown in this paper that using the proposed reset element architecture, CgLp gets closer to its ideal behaviour for a range of frequencies, and its performance will be improved accordingly.
Multi-degree-of-freedom systems with a Coulomb friction contact: analytical boundaries of motion regimes
Authors: Marino Luca , Cicirello Alice 
Published: March 2021

AbstractThis paper proposes an approach for the determination of the analytical boundaries of continuous, stick-slip and no motion regimes for the steady-state response of a multi-degree-of-freedom (MDOF) system with a single Coulomb contact to harmonic excitation. While these boundaries have been previously investigated for single-degree-of-freedom (SDOF) systems, they are mostly unexplored for MDOF systems. Closed-form expressions of the boundaries of motion regimes are derived and validated numerically for two-degree-of-freedom (2DOF) systems. Different configurations are observed by changing the mass in contact and by connecting the rubbing wall to: (i) the ground, (ii) the base or (iii) the other mass. A procedure for extending these results to systems with more than 2DOFs is also proposed for (i)–(ii) and validated numerically in the case of a 5DOF system with a ground-fixed contact. The boundary between continuous and stick-slip regimes is obtained as an extension of Den Hartog’s formulation for SDOF systems with Coulomb damping (Trans Am Soc Mech Eng 53: 107–115, 1931). The boundary between motion and no motion regimes is derived with an ad hoc procedure, based on the comparison between the overall dynamic load and the friction force acting on the mass in contact. The boundaries are finally represented in a two-dimensional parameter space, showing that the shape and the extension of the regions associated with the three motion regimes can change significantly when different physical parameters and contact configurations are considered.
Some double-angle formulas related to a generalized lemniscate function
Authors: Takeuchi Shingo 
Published: March 2021

AbstractIn this paper, we will establish some double-angle formulas related to the inverse function of $$\int _0^x \text {d}t/\sqrt{1-t^6}$$

∫
0
x

d
t
/

1
-

t
6

. This function appears in Ramanujan’s Notebooks and is regarded as a generalized version of the lemniscate function.
Burst Detection by Water Demand Nowcasting Based on Exogenous Sensors
Authors: Geelen Caspar V. C. , Yntema Doekle R. , Molenaar Jaap , Keesman Karel J. 
Published: March 2021

AbstractBursts of drinking water pipes not only cause loss of drinking water, but also damage below and above ground infrastructure. Short-term water demand forecasting is a valuable tool in burst detection, as deviations between the forecast and actual water demand may indicate a new burst. Many of burst detection methods struggle with false positives due to non-seasonal water consumption as a result of e.g. environmental, economic or demographic exogenous influences, such as weather, holidays, festivities or pandemics. Finding a robust alternative that reduces the false positive rate of burst detection and does not rely on data from exogenous processes is essential. We present such a burst detection method, based on Bayesian ridge regression and Random Sample Consensus. Our exogenous nowcasting method relies on signals of all nearby flow and pressure sensors in the distribution net with the aim to reduce the false positive rate. The method requires neither data of exogenous processes, nor extensive historical data, but only requires one week of historical data per flow/pressure sensor. The exogenous nowcasting method is compared with a common water demand forecasting method for burst detection and shows sufficiently higher Nash-Sutcliffe model efficiencies of 82.7% - 90.6% compared to 57.9% - 77.7%, respectively. These efficiency ranges indicate a more accurate water demand prediction, resulting in more precise burst detection.
Toxicity mitigation by N-acetylcysteine and synergistic toxic effect of nano and bulk ZnO to Panagrellus redivivus
Authors: Kiss Lola Virág , Sávoly Zoltán , Ács András , Seres Anikó , Nagy Péter István 
Published: March 2021

AbstractTo better understand the nanosize-relevant toxic effects and underlying mechanisms, N-acetylcysteine (NAC), as a mitigation agent, an ionic form of Zn (ZnCl2), and the binary mixture of ZnO with different particle sizes (15 nm and 140 nm), was used in toxicity assays with the nematode Panagrellus redivivus. The ZnCl2 concentrations were applied to show the amount of dissolved Zn ions present in the test system. Reactive oxygen species (ROS) measuring method was developed to fit the used test system. Our studies have shown that NAC can mitigate the toxic effects of both studied particle sizes. In the applied concentrations, ZnCl2 was less toxic than both of the ZnO particles. This finding indicates that not only ions and ROS produced by the dissolution are behind the toxic effects of the ZnO NPs, but also other particle size-dependent toxic effects, like the spontaneous ROS generation, are also relevant. When the two materials were applied in binary mixtures, the toxic effects increased significantly, and the dissolved zinc content and the ROS generation also increased. It is assumed that the chemical and physical properties of the materials have been mutually reinforcing to form a more reactive mixture that is more toxic to the P. redivivus test organism. Our findings demonstrate the importance of using mitigation agent and mixtures to evaluate the size-dependent toxicity of the ZnO.
Graphical abstract
Correlation between polio immunization coverage and overall morbidity and mortality for COVID-19: an epidemiological study
Authors: Afify Marwa Adel , Alqahtani Rakan M. , Alzamil Mohammed Abdulrahman Mohammed , Khorshid Faten Abdulrahman , Almarshedy Sumayyah Mohammad , Alattas Sana Ghazi , Alrawaf Talal Nabeel , Bin-Jumah May , Abdel-Daim Mohamed M. , Almohideb Mohammad 
Published: March 2021

AbstractWe conducted the current analysis to determine the potential role of polio vaccination in the context of the spread of COVID-19. Data were extracted from the World Health Organization’s (WHO) Global Health Observatory data repository regarding the polio immunization coverage estimates and correlated to the overall morbidity and mortality for COVID-19 among different countries. Data were analyzed using R software version 4.0.2. Mean and standard deviation were used to represent continuous variables while we used frequencies and percentages to represent categorical variables. The Kruskal-Wallis H test was used for continuous variables since they were not normally distributed. Moreover, the Spearman rank correlation coefficient (rho) was used to determine the relationship between different variables. There was a significantly positive correlation between the vaccine coverage (%) and both of total cases per one million populations (rho = 0.37; p-value < 0.001) and deaths per one million populations (rho = 0.30; p-value < 0.001). Moreover, there was a significant correlation between different income groups and each of vaccine coverage (%) (rho = 0.71; p-value < 0.001), total cases per one million populations (rho = 0.50; p-value < 0.001), and deaths per one million populations (rho = 0.39; p-value < 0.001). All claims regarding the possible protective effect of Polio vaccination do not have any support when analyzing the related data. Polio vaccination efforts should be limited to eradicate the disease from endemic countries; however, there is no evidence to support the immunization with live-attenuated vaccines for the protection against COVID-19.
Maternal exposure to O3 and NO2 may increase the risk of newborn congenital hypothyroidism: a national data-based analysis in China
Authors: Qi Cuifang , Shang Li , Yang Wenfang , Huang Liyan , Yang Liren , Xin Juan , Wang Shanshan , Yue Jie , Zeng Lingxia , Chung Mei Chun 
Published: March 2021

AbstractMaternal exposure to air pollution during pregnancy is associated with adverse outcomes in the offspring, but limited studies focused on the impacts of gaseous air pollution on newborn congenital hypothyroidism (CH). Therefore, a national data-based analysis was conducted to explore the association between maternal exposure to gaseous air pollution and the incidence of CH in China. Annual average exposure levels of SO2, NO2, CO, and O3 from January 1, 2014, to December 30, 2014, were acquired from the Chinese Air Quality Online Monitoring and Analysis Platform. The annual incidence of newborn CH from October 1, 2014, to September 30, 2015, was collected from the Chinese Maternal and Child Health Surveillance Network. Temperature and toxic metal in wastewater in 2014 were also collected as covariates. Maternal exposure to O3 and NO2 in 1 μg/m3 level increment was positively associated with newborn CH, with an OR of 1.055 (95% CI 1.011, 1.102) and 1.097 (95% CI 1.019, 1.182) after adjusting for covariates completely. Compared with the lowest level of O3, maternal exposure to the 4th quartile of O3 was positively associated with newborn CH (OR 1.393, 95% CI 1.081, 1.794) after adjusting for covariates completely. And the 3rd and 4th quartiles of NO2 were associated positively with CH (OR 1.576, 95% CI 1.025, 2.424, and OR 1.553, 95% CI 0.999, 2.414, respectively) compared with the lowest level of NO2. By fitting the ROC curve, 93.688 μg/m3 in O3 might be used as cutoff to predict the incidence of newborn CH in China.
Managing performance and winning trust: how World Bank staff shape recipient performance
Authors: Heinzel Mirko , Liese Andrea 
Published: March 2021

AbstractWorld Bank evaluations show that recipient performance varies substantially between different projects. Extant research has focused on country-level variables when explaining these variations. This article goes beyond country-level explanations and highlights the role of World Bank staff. We extend established arguments in the literature on compliance with the demands of International Organizations (IOs) and hypothesize that IO staff can shape recipient performance in three ways. First, recipient performance may be influenced by the quality of IO staff monitoring and supervision. Second, the leniency and stringency with which IO staff apply the aid agreement could improve recipient performance. Third, recipient performance may depend on whether IO staff can identify and mobilize supportive interlocutors through their networks in the recipient country. We test these arguments by linking a novel database on the tenure of World Bank task team leaders to projects evaluated between 1986 and 2020. The findings are consistent with the expectation that World Bank staff play an important role, but only in investment projects. There is substantial evidence that World Bank staff supervisory ability and country experience are linked to recipient performance in those projects. Less consistent evidence indicates that leniency could matter. These findings imply that World Bank staff play an important role in facilitating implementation of investment projects.
Improving machinability of additively manufactured components with selectively weakened material
Authors: Maucher Clemens , Teich Heiko , Möhring Hans-Christian 
Published: March 2021

AbstractPart design and the possibilities of production are disrupted by the increased usage of additive manufacturing (AM). Featuring excellent creative freedom due to the layer-by-layer buildup of components, AM leads to profound changes in future part design and enables previously impossible geometries. Laser powder bed fusion (LPBF) technology already allows to manufacture small quantities of parts with high productivity and material efficiency. Due to the specific process characteristics, the resulting surface finish of these parts is insufficient for a wide range of applications, and post-processing is usually unavoidable. Specifically for functional surfaces, this post-processing is often done by machining processes, which can pose challenges for intricate and complex AM parts due to excessive machining forces. In the present paper, the influence and the possibilities of the LPBF process parameters on the subtractive post-processing are shown. A novel weakened structure is developed to selectively reduce the strength of the material and improve the cutting conditions. Chip formation, cutting forces and vibrations during drilling as well as cutting forces during an orthogonal cut are examined. To quantify the differences, a comparison of the machinability between bulk material, standard support structures and the weakened structure is carried out.
Local Regularity for the Harmonic Map and Yang–Mills Heat Flows
Authors: Afuni Ahmad 
Published: March 2021

AbstractWe establish new local regularity results for the harmonic map and Yang–Mills heat flows on Riemannian manifolds of dimension greater than 2 and 4, respectively, obtaining criteria for the smooth local extensibility of these flows. As a corollary, we obtain new characterisations of singularity formation and use this to obtain a local estimate on the Hausdorff measure of the singular sets of these flows at the first singular time. Finally, we show that smooth blow-ups at rapidly forming singularities of these flows are necessarily nontrivial and admit a positive lower bound on their heat ball energies. These results crucially depend on some local monotonicity formulæ for these flows recently established by Ecker (Calc Var Partial Differ Equ 23(1):67–81, 2005) and the Afuni (Calc Var 555(1):1–14, 2016; Adv Calc Var 12(2):135–156, 2019).