bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multilingual audio information management system based on semantic knowledge in complex environments
Authors: Lopez-de-Ipina Karmele , Barroso Nora , Calvo Pilar M. , Hernandez Carmen , Ezeiza Aitzol , Susperregi Unai , Fernández Elsa 
Published: February 2020

AbstractThis paper proposes a multilingual audio information management system based on semantic knowledge in complex environments. The complex environment is defined by the limited resources (financial, material, human, and audio resources); the poor quality of the audio signal taken from an internet radio channel; the multilingual context (Spanish, French, and Basque that is in under-resourced situation in some areas); and the regular appearance of cross-lingual elements between the three languages. In addition to this, the system is also constrained by the requirements of the local multilingual industrial sector. We present the first evolutionary system based on a scalable architecture that is able to fulfill these specifications with automatic adaptation based on automatic semantic speech recognition, folksonomies, automatic configuration selection, machine learning, neural computing methodologies, and collaborative networks. As a result, it can be said that the initial goals have been accomplished and the usability of the final application has been tested successfully, even with non-experienced users.
Implementation of cisternostomy as adjuvant to decompressive craniectomy for the management of severe brain trauma
Authors: Giammattei Lorenzo , Starnoni Daniele , Maduri Rodolfo , Bernini Adriano , Abed-Maillard Samia , Rocca Alda , Cossu Giulia , Simonin Alexandre , Eckert Philippe , Bloch Jocelyne , Levivier Marc , Oddo Mauro , Messerer Mahmoud , Daniel Roy Thomas 
Published: February 2020

Abstract
Objective
To evaluate the value of an adjuvant cisternostomy (AC) to decompressive craniectomy (DC) for the management of patients with severe traumatic brain injury (sTBI).

Methods
A single-center retrospective quality control analysis of a consecutive series of sTBI patients surgically treated with AC or DC alone between 2013 and 2018. A subgroup analysis, “primary procedure” and “secondary procedure”, was also performed. We examined the impact of AC vs. DC on clinical outcome, including long-term (6 months) extended Glasgow outcome scale (GOS-E), the duration of postoperative ventilation, and intensive care unit (ICU) stay, mortality, Glasgow coma scale at discharge, and time to cranioplasty. We also evaluated and analyzed the impact of AC vs. DC on post-procedural intracranial pressure (ICP) and brain tissue oxygen (PbO2) values as well as the need for additional osmotherapy and CSF drainage.

Results
Forty patients were examined, 22 patients in the DC group, and 18 in the AC group. Compared with DC alone, AC was associated with significant shorter duration of mechanical ventilation and ICU stay, as well as better Glasgow coma scale at discharge. Mortality rate was similar. At 6-month, the proportion of patients with favorable outcome (GOS-E ≥ 5) was higher in patients with AC vs. DC [10/18 patients (61%) vs. 7/20 (35%)]. The outcome difference was particularly relevant when AC was performed as primary procedure (61.5% vs. 18.2%; p = 0.04). Patients in the AC group also had significant lower average post-surgical ICP values, higher PbO2 values and required less osmotic treatments as compared with those treated with DC alone.

Conclusion
Our preliminary single-center retrospective data indicate that AC may be beneficial for the management of severe TBI and is associated with better clinical outcome. These promising results need further confirmation by larger multicenter clinical studies. The potential benefits of cisternostomy should not encourage its universal implementation across trauma care centers by surgeons that do not have the expertise and instrumentation necessary for cisternal microsurgery. Training in skull base and vascular surgery techniques for trauma care surgeons would avoid the potential complications associated with this delicate procedure.
Laser beam scattering for the detection of flat, curved, smooth, and rough microplastics in water
Authors: Asamoah Benjamin O. , Amoani James , Roussey Matthieu , Peiponen Kai-Erik 
Published: February 2020

AbstractMicroplastic (MP) pollution is alarming and poses an imminent threat to the environment with a direct impact on our health and that of fauna in natural water bodies. The understanding of light–MP interactions in water as well as the need for low-cost and robust optical sensors for the detection of MPs that appear everywhere is, therefore, necessary. We have demonstrated the use of a prototype optical sensor in the detection of flat and curved [from polyethylene terephthalate (PET) water bottle] pristine and rough MPs from commercial PET and low-density polyethylene plastics in water. The optical sensor utilizes a photodiode and charge-coupled device (CCD) camera to record simultaneously the specular reflection and the speckle pattern modified by the MPs. In this study, we have exploited the specular reflection in the detection of the pristine samples, whereas the speckle contrast, the normalized standard deviation of the speckle pattern intensity, is utilized in the qualitative estimation of the “effective” surface roughness of the MPs. With the sensor, one can, therefore, detect PET MPs with varying average surface roughness, Ra an indication of MP aging, embedded in water. The prototype can detect the effect of size, type, curvature, transparency, and the translucency of sunken and/or floating MPs in water based on the reflection, scattering, and the (edge) diffraction of light. However, the optical sensor is limited in the discrimination of MP concentration in water. Further modifications to the sensor are needed for its practical implementation in complex natural water bodies and wastewaters.
The examination of the effect of the criterion for neural network’s learning on the effectiveness of the qualitative analysis of multidimensional data
Authors: Jamróz Dariusz 
Published: February 2020

AbstractA variety of multidimensional visualization methods are applied for the qualitative analysis of multidimensional data. One of the multidimensional data visualization methods is a method using autoassociative neural networks. In order to perform visualizations of n-dimensional data, such a network has n inputs, n outputs and one of the interlayers consisting of two outputs whose values represent coordinates of the analyzed sample’s image on the screen. Such a criterion for the network’s learning consists in that the same value as the one at the ith input appears at each ith output. If the network is trained in this way, the whole information from n inputs was compressed to two outputs of the interlayer and then decompressed to n network outputs. The paper shows the application of different learning criteria can be more beneficial from the point of view of the results’ readability. Overall analysis was conducted on seven-dimensional real data representing three coal classes, five-dimensional data representing printed characters, 216-dimensional data representing hand-written digits and, additionally, in order to illustrate additional explanations using artificially generated seven-dimensional data. Readability of results of the qualitative analysis of these data was compared using the multidimensional visualization utilizing neural networks for different learning criteria. Also, the obtained results of applying all analyzed criteria on 20 randomly selected sets of multidimensional data obtained from one of the publicly available repositories are presented.
Observations on the May 2019 Joffre Peak landslides, British Columbia
Authors: Friele Pierre , Millard Tom H. , Mitchell Andrew , Allstadt Kate E. , Menounos Brian , Geertsema Marten , Clague John J. 
Published: February 2020

AbstractTwo catastrophic landslides occurred in quick succession on 13 and 16 May 2019, from the north face of Joffre Peak, Cerise Creek, southern Coast Mountains, British Columbia. With headscarps at 2560 m and 2690 m elevation, both began as rock avalanches, rapidly transforming into debris flows along middle Cerise Creek, and finally into debris floods affecting the fan. Beyond the fan margin, a flood surge on Cayoosh Creek reached bankfull and attenuated rapidly downstream; only fine sediment reached Duffey Lake. The toe of the main debris flow deposit reached 4 km from the headscarp, with a travel angle of 0.28, while the debris flood phase reached the fan margin 5.9 km downstream, with a travel angle of 0.22. Photogrammetry indicates the source volume of each event is 2–3 Mm3, with combined volume of 5 Mm3. Lidar differencing, used to assess deposit volume, yielded a similar total result, although error in the depth estimate introduced large volume error masking the expected increase due to dilation and entrainment. The average velocity of the rock avalanche-debris flow phases, from seismic analysis, was ~ 25–30 m/s, and the velocity of the 16 May debris flood on the upper fan, from super-elevation and boulder sizes, was 5–10 m/s. The volume of debris deposited on the fan was ~ 104 m3, 2 orders of magnitude less than the avalanche/debris flow phases. Progressive glacier retreat and permafrost degradation were likely the conditioning factors; precursor rockfall activity was noted at least ~6 months previous; thus, the mountain was primed to fail. The 13 May landslide was apparently triggered by rapid snowmelt, with debuttressing triggering the 16 May event.
Spectral estimates and discreteness of spectra under Riemannian submersions
Authors: Polymerakis Panagiotis 
Published: February 2020

AbstractFor Riemannian submersions, we establish some estimates for the spectrum of the total space in terms of the spectrum of the base space and the geometry of the fibers. In particular, for Riemannian submersions of complete manifolds with closed fibers of bounded mean curvature, we show that the spectrum of the base space is discrete if and only if the spectrum of the total space is discrete.
Experimental Determination of the Mechanical Properties and Deformation Constants of Mórágy Granitic Rock Formation (Hungary)
Authors: Davarpanah M. , Somodi G. , Kovács L. , Vásárhelyi B. 
Published: February 2020

AbstractDetermination of the mechanical behaviour of intact rock is one of the most important parts of any engineering projects in the field of rock mechanics. The most important mechanical parameters required to understand the quality of intact rock are Young’s modulus (E), Poisson’s ratio (ν), the strength of rock (σc) and the ratio of Young’s modulus to the strength of rock known as modulus ratio (MR), which can be used for calculations. The particular interest of this paper is to investigate the relationship between these parameters for Hungarian granitic rock samples. To fulfil this aim, Modulus of elasticity (E), Modulus of rigidity (G), Bulk modulus (K) and the modulus ratio (MR = E/σc) of 50 granitic rock samples collected from Bátaapáti radioactive waste repository were examined. Fifty high-precision uniaxial compressive tests were conducted on strong (σc > 100 MPa) rock samples, exhibiting the wide range of elastic modulus (E = 57.425–88.937 GPa), uniaxial compressive strength (σc = 133.34–213.04 MPa) and Poisson’s ratio (ν = 0.18–0.32). The observed value (MR = 326–597) and mean value of MR = 439.4 are compared with the results of similar previous researches. Moreover, the statistical analysis for all studied rocks was performed and the relationship between MR and other mechanical parameters such as maximum axial strain (εa, max) for studied rock samples was discussed. Finally, the validity of the proposed mathematical model by Palchik (Geomech Geophys Geo-energy Geo-resour 6:1–12, 2019) for stress–strain behaviour of granitic rock samples was investigated.
A data-driven procedure to determine the bunching window: an application to the Netherlands
Authors: Bosch Nicole , Dekker Vincent , Strohmaier Kristina 
Published: February 2020

AbstractWe extend the bunching approach introduced by Saez (Am Econ J Econ Policy 2:180–212, 2010) by proposing an intuitive, data-driven procedure to determine the bunching window. By choosing the bunching window ad hoc, researchers throw away informative data points for estimating the counterfactual income distribution in the absence of the kink. Assuming a descending bunching mass to both sides of the threshold, the proposed algorithm produces a distribution of lower and upper bounds for the bunching window. In each iteration, the bunching window is defined as all contiguous bin midpoints around the threshold that lie outside of the confidence band resulting from running a local regression through all data points outside of the excluded region. Monte Carlo simulations provide evidence that our data-driven procedure outperforms larger bunching windows in terms of bias and efficiency. In our application for the Netherlands, we find clear evidence of bunching behaviour at all three thresholds of the Dutch tax schedule with a precisely estimated elasticity of 0.023 at the upper threshold, which is driven by self-employed, women and joint tax filers.
Substantial understory contribution to the C sink of a European temperate mountain forest landscape
Authors: Dirnböck T. , Kraus D. , Grote R. , Klatt S. , Kobler J. , Schindlbacher A. , Seidl R. , Thom D. , Kiese R. 
Published: February 2020

AbstractContextThe contribution of forest understory to the temperate forest carbon sink is not well known, increasing the uncertainty in C cycling feedbacks on global climate as estimated by Earth System Models.ObjectivesWe aimed at quantifying the effect of woody and non-woody understory vegetation on net ecosystem production (NEP) for a forested area of 158 km2in the European Alps.MethodsWe simulated C dynamics for the period 2000–2014, characterized by above-average temperatures, windstorms and a subsequent bark beetle outbreak for the area, using the regional ecosystem model LandscapeDNDC.ResultsIn the entire study area, woody and non-woody understory vegetation caused between 16 and 37% higher regional NEP as compared to a bare soil scenario over the 15-year period. The mean annual contribution of the understory to NEP was in the same order of magnitude as the average annual European (EU-25) forest C sink. After wind and bark beetle disturbances, the understory effect was more pronounced, leading to an increase in NEP between 35 and 67% compared to simulations not taking into account these components.ConclusionsOur findings strongly support the importance of processes related to the understory in the context of the climate change mitigation potential of temperate forest ecosystems. The expected increases in stand replacing disturbances due to climate change call for a better representation of understory vegetation dynamics and its effect on the ecosystem C balance in regional assessments and Earth System Models.
A machine learning approach to univariate time series forecasting of quarterly earnings
Authors: Fischer Jan Alexander , Pohl Philipp , Ratz Dietmar 
Published: February 2020

AbstractWe propose our quarterly earnings prediction (QEPSVR) model, which is based on epsilon support vector regression (ε-SVR), as a new univariate model for quarterly earnings forecasting. This follows the recommendations of Lorek (Adv Account 30:315–321, 2014.10.1016/j.adiac.2014.09.008), who notes that although the model developed by Brown and Rozeff (J Account Res 17:179–189, 1979) (BR ARIMA) is advocated as still being the premier univariate model, it may no longer be suitable for describing recent quarterly earnings series. We conduct empirical studies on recent data to compare the predictive accuracy of the QEPSVRmodel to that of the BR ARIMA model under a multitude of conditions. Our results show that the predictive accuracy of the QEPSVRmodel significantly exceeds that of the BR ARIMA model under 24 out of the 28 tested experiment conditions. Furthermore, significance is achieved under all conditions considering short forecast horizons or limited availability of historic data. We therefore advocate the use of the QEPSVRmodel for firms performing short-term operational planning, for recently founded companies and for firms that have restructured their business model.
Soziotechnische Analyse und Gestaltung von Virtualisierungsprozessen
Authors: Paulsen Hilko , Zorn Victoria , Inkermann David , Reining Nine , Baschin Julian , Vietor Thomas , Kauffeld Simone 
Published: February 2020

ZusammenfassungDieses Praxisbeispiel der Zeitschrift „Gruppe. Interaktion. Organisation (GIO)“ betrachtet den Fall einer virtuellen Inbetriebnahme bei einem Unternehmen aus dem Anlagen- und Maschinenbau aus soziotechnischer Systemperspektive. In einer digitalisierten Arbeitswelt werden Tätigkeiten zunehmend in den virtuellen Raum verlagert, sodass mit Hilfe digitale Abbilder beispielsweise Simulationen durchgeführt werden können. Bevor die Maschine real in Betrieb genommen wird, soll die Inbetriebnahme durch eine Simulation mittels Software erfolgen. Das Zusammenspiel der Steuerungssoftware und Hardwarekomponenten einer Maschine wird dabei mit dem Ziel, Fehler und Probleme frühzeitiger zu erkennen, simuliert und geprüft. Diese neue Entwicklungstechnologie und deren Implementierung in den Produktentwicklungsprozess wird vor dem Hintergrund eines soziotechnischen Systemverständnisses reflektiert. Im Praxisbeispiel erfolgt eine Analyse und Gestaltung von Mensch, Technik und Organisation sowie deren Wechselspiel. Es zeigt sich, dass die virtuelle Inbetriebnahme simultane Entwicklungsprozesse bei der Bearbeitung von Kundenaufträgen sowie dadurch eine stärkere modulartige Vernetzung der beteiligten Entwicklungsdomänen nahelegt. Diese Prozesse gehen mit erhöhten Anforderungen an die Mitarbeitenden in Bezug auf Medienkompetenzen sowie Selbstkompetenzen einher.
Temperature-Dependent Misfit Stress in Gamma Double Prime Strengthened Ni-Base Superalloys
Authors: Zhang R. Y. , Qin H. L. , Bi Z. N. , Li J. , Paul S. , Lee T. L. , Zhang S. Y. , Zhang J. , Dong H. B. 
Published: February 2020

Abstract
Misfit stresses in the γ″-strengthened Ni-base superalloy Inconel 718 were calculated from the measured constrained misfit strain using Eshelby’s inclusion method. The constrained misfit strains of the γ″ precipitates were measured using neutron diffraction at various temperatures with the aid of the stress-induced variant selection method. Eshelby tensor was calculated using the expressions for the case of anisotropic matrix given by Mura. Results show the presence of significant compressive misfit stresses in the γ″ precipitates with an anisotropic distribution, namely 3.0 GPa along the habit plane and 1.7 GPa along the plane normal direction at room temperature, and 2.0 and 1.2 GPa at 664 °C. The decrease in misfit stresses was due to the decrease in stiffness and the different coefficients of thermal expansion of the γ and γ″ phases. The average internal stresses in the γ matrix due to lattice misfit were found to be ~ 329 MPa at room temperature and ~ 186 MPa at 664 °C in tension. The possibility of relieving such high levels of misfit stresses in precipitates by loss of coherency during continued growth of precipitates is also discussed.
Continuation of fishing subsistence in the Ukrainian Neolithic: diet isotope studies at Yasinovatka, Dnieper Rapids
Authors: Budd Chelsea , Potekhina Inna , Lillie Malcolm 
Published: February 2020

AbstractYasinovatka is one of around 30 prehistoric cemetery sites of fisher-hunter-foragers located along the Dnieper River in southern Ukraine. Dating toc.5540–4930 cal BC, the skeletal remains at Yasinovatka suggest that around sixty-eight individuals were interred at the cemetery, during three broad phases of interment: A-type burials (c. 5540–4930 cal BC), Ƃ1 pit burials (c. 5550–4750 cal BC), and Ƃ2 pit burials (c. 4980–4460 cal BC). The burials are characterized, in part, by the inclusion of a number of Mariupol-type plates of boar tusk, in addition to deer tooth pendants, Unio shells, knife-like flint blades,Cyprinidaeteeth, sherds of Neolithic pottery, and significant deposits of ochre in the later burial pits. Here we analyse δ13C and δ15N values for 50 human bone collagen samples from the site. The majority of the isotope results show a fisher-hunter-forager population reliant predominantly on freshwater aquatic proteins, which is in keeping with previous dietary isotope studies in the area. Two individuals however have δ15N values that are clearly depleted when compared with the main population; these reflect dietary protein intakes based on plant and animal terrestrial resources rather than the predominant focus on aquatic resources. Notably, the δ13C values of these anomalous individuals are not enriched compared with the fauna samples analysed from the region; this supports the possibility that they were incomers to the area, potentially from a nearby agrarian population.
Predictive model for multistage cyber-attack simulation
Authors: Kour Ravdeep , Thaduri Adithya , Karim Ramin 
Published: February 2020

AbstractAdoption of information and communication technologies (ICT) in railway has improved the reliability, maintainability, operational efficiency, capacity as well as the comfort of passengers. This adoption introduces new vulnerabilities and entry points for hackers to launch attacks. Advanced cybersecurity threats with automated capabilities are increasing in such sectors as finance, health, grid, retail, government, telecommunications, transportation, etc. These cyber threats are also increasing in railways and, therefore, it needs for cybersecurity measures to predict, detect and respond these threats. The cyber kill chain (CKC) model is a widely used model to detect cyber-attacks and it consists of seven stages/chains; breaking the chain at an early stage will help the defender stop the adversary’s malicious actions. Due to lack of real cybersecurity data, this research simulates cyber-attacks to calculate the attack penetration probabilities at each stage of the cyber kill chain model. The objective of this research is to predict cyber-attack penetrations by implementing various security controls using modeling and simulation. This research is an extension of developed railway defender kill chain which provides security controls at each stage of CKC for railway organizations to minimize the risk of cyber threats.