dataesr/scientific-paragraphs-categorization huggingface dataset:
The uncertainty components related to dead time and coincidence resolving time were conservatively estimated in the case of 4πβ(LS)-γ coincidence counting. The 4KAM module uses different techniques to determine the coincidences for the beta channels (D and T) and β-γ coincidences. The  former are realized by a delay line with increments of 2 ns while the latter are bound to the FPGA clock, resulting in a jitter and increments of about 5. 882 ns. Further investigation may help to reduce these uncertainty components in the future.
The LS data were then analysed using different combinations of beta spectra calculation and the kB parameter. The activity concentration obtained from all individual LS samples was calculated for each configuration. The results were then compared with the reference activity concentration a = 143. 571(35) kBq g -1 , which corresponds to the weighted mean of the two coincidence counting methods. Fig. 6  shows the relative deviation between individual results of the LS samples and the reference value as a function of the 60 Co counting efficiency. At the beginning, the classical beta spectrum and a parameter kB = 0. 0075 cm MeV -1 were used (Fig. 6a ). The LS results are significantly lower than the reference value. The deviations increase at lower 60 Co counting efficiencies. It is to be noted that the activity concentration derived from the CIEMAT/NIST efficiency tracing is considerably lower than the results from TDCR.
Scanning Electron Microscopy Second electrons images of diabolo fracture surfaces were stored with a JSM JEOL 7100 F scanning electron microscope (SEM). In addition, the SEM is coupled with an Oxford Instrument X Max Energy Dispersive Spectrometer of X-rays (EDS) and an Aztzec software in order to determine the surface fracture composition, especially in the crack initiation zone. The fracture surfaces to be analysed were previously metallized by vapour deposition of an Au-Pd layer.
Acknowledgements The authors thank the  Cooper Standard France company  for supporting this work and for fruitful discussions. The authors thank also the  National Center for Scientific Research (MRCT-CNRS  and  MI-CNRS ) and  Rennes Metropole  for supporting this work financially. SEM images were performed at  CMEBA facility (ScanMAT, University of Rennes 1 ) which received a financial support from the  European Union  ( CPER-FEDER 2007-2014 ).
B. The maritime SOC On the shore side, the network flows usually either exit at the fleet management centre or at the SOC, either hosted or at the sub contractor premises. After the possible crypto equipment used for deciphering, the first block is the Ship Shore Manager (SSM). It completes the specific channel between SSMs, ensuring all collected data on board properly exits on the shore side as expected, in a timely and ordered manner, and within the specified bandwidth limits. Then, the second block is the Central Processor (CP). All metadata, logs and alerts flowing from remote sites are centralized on the CP where they are pipelined, filtered, normalized or transformed as needed by the SOC. The third block is the Data Store (DS). Traditionally, this can be a big data engine, enabling the secured storage of data and its indexing for efficient queries.
First results of parametric studies To better understand the behavior of the reduced order model according to its inner parameters such that the numbers of clusters or the number of computations in the training set, some convergence studies have been led. The used test-case is the one presented in the section 2. There are 29 computations available on which the quality of the interpolation of the reduced order model will be evaluated. The first 25 simulations have been chosen according to a Latin Hypercube Sampling design of experiments. The last 4 configurations correspond to 4 corners of the design space. It is remind that there are 16878 nodes and 76 instants in the finite element model. For information, the highfidelity computations take about 15 minutes using the fast dynamics software VPS of ESI Group.
3 fields were reduced: local displacements along X, Y and Z. Shell thickness was used as parameter field. Thicknesses were projected on the nodes. 200 clusters along the columns (nodes) and 20 clusters along the lines (instants) per fields were chosen using k-means method. A proportion of 5E-6 of the total constraints were kept. In total 3060 constraints were used in the second model. Also, hard constraints on 7 points of interest (along known structural position or used for the calculation of objectives functions) were imposed for each field at initial and final instants. The imposed εmax was 0. 05. The data were normalized as in the previous test-case. The second reduction (ROM-2) ran in 12 hours using 300 GB of RAM. The regression found 21, 38 and 32 non-null coefficients for the X,Y and Z respectively among the 291,600 possible coefficients.
Conclusion In this article, construction of a reduced order model called ReCUR has been outlined as well as its use to estimate new technical solutions. It consists in a regression model coupled with a low rank tensor approximation method. The two application examples show the potential of the method in the context of the fast dynamic simulations. It allows, indeed, to make evaluation in a few minutes for industrial test-cases, with still large potential for code optimization and parallelization to improve efficiency. The domain of application is crash simulation, however the method is not limited to this physic. The method may be useful as soon as time consuming high-fidelity computations are required in a design process. Potential domain can then be combustion simulations or fluid mechanics among others.
Acknowledgements This research work has been carried out in the framework of the  ROM  project  at IRT SystemX ,  Paris-Saclay , France, and therefore granted with public funds within the scope of the  French Program "Investissements d'Avenir ". Acknowledgements : This research work has been carried out in the framework of  IRT SystemX, Paris-Saclay, France , and therefore granted with public funds within the scope of the  French Program "Investissements d'Avenir ". It has been part of the  ROM  project. Vitae :  Yves Le Guennec :  Yves Le Guennec  holds a PhD in numerical and structural mechanics. He is a research engineer at the  Technological Research Institute SystemX. Involved in the project  ROM (Multiphysic 's reduction and optimization), he focuses his research on the optimization under uncertainties and non-intrusive reduced order models.
The model of  Kumbhakar, Lien and Hardaker (2014)  allows us to estimate and disentangle persistent efficiency and transient efficiency. 2 ilippini and  Greene (2016)  find that this approach provides new and more precise estimates. The persistent efficiency estimate provides a new measure of efficiency which is not related to the estimate provided by the approach of  Battese and Coelli (1995). The estimate of the transient inefficiency, while more closely related to the one obtained using the approach of  Greene (2005) , provides useful additional information on short-term inefficiency. We consider a large and unique dataset of 166 banks for the period 2008-2015, including the Big Five banks, joint-stock commercial banks, city commercial banks, rural banks and foreign banks. We hand-collect data from banks annual reports to extend the coverage of our dataset.
We rely on the panel nature of our dataset to examine the roots of Chinese banks inefficiency and assess whether lower efficiency for the Big Five banks is observed for both persistent and transient components. Our paper contributes to the analysis of the efficiency of Chinese banks. Our results help better understand the gap in efficiency of the Big Five banks and demonstrate the application of the stochastic frontier model in separating persistent bank efficiency from transient bank efficiency. In terms of methodology, this paper also complements the recent work of  Badunenko and Kumbakhar (2017)  on disentangling persistent and transient efficiency in the Indian banking industry. The rest of the article is structured as follows. Section 2 provides the overview of the Chinese banking sector and reviews the related literature.
Efficiency in Chinese banking Several studies investigate the efficiency of Chinese banks. Chen, Skully and Brown (2005)  investigate the impact of the 1995 bank deregulation on the cost efficiency of Chinese banks. Estimating the cost efficiency of 43 Chinese banks over the period 1993-2000 with nonparametric data envelopment analysis (DEA), they find that large state-owned banks and small joint-stock commercial banks are more efficient than medium-sized joint-stock commercial banks. The mean yearly cost efficiency scores for the whole sample range from 42. 6% to 58. 2%. Fu and Heffernan (2007)  estimate the cost efficiency of Chinese banks over the period 1985-2002, employing the stochastic frontier analysis (SFA). Their sample contains 14 banks (four state-owned banks and ten joint-stock commercial banks).
Data Our analysis employs a unique dataset containing a total of 974 observations of 166 banks, covering the period 2008-2015. We use hand-collected data from the annual reports of   1  and 2. We observe that the price of physical capital is much higher for foreign banks than for the other banks. This can be explained by the fact that the foreign banks have a small market share all around the country and their customers are mainly foreign companies. As such they do not have a large network of branches and therefore have lower fixed assets on average than the other banks. In addition they are mainly located in very large cities associated with higher operating costs for the offices. Our finding of higher price of physical capital accords with  Dong et al. (2016)  who report the mean price of physical capital for big banks, medium banks, and small banks, the latter category combining foreign banks and city commercial banks, and observe a much higher mean price for the latter category of banks.
the relevant bank websites to supplement yearly bank-level financial statement data of Chinese banks from BankScope database. Our sample encompasses the majority of the Chinese banking sector's assets. We omit earlier time periods as data are only available for a limited number of banks. To put our dataset into perspective; Berger, Hasan and Zhou (2009) use a 38-bank sample in their efficiency analysis, and Dong et al. (2016) a 142-bank sample in their investigation of cost and profit efficiency. The banks in our sample are divided into five categories based on ownership structure: the Big Five banks, joint-stock commercial banks (JSCB), city commercial banks (CCB), rural commercial banks (RCB) and foreign banks. This division follows the CBRC classifications. The descriptive statistics of the main variables used in the analysis are provided in Tables.
Graph aggregation is the process of computing a single output graph that constitutes a good compromise between several input graphs, each provided by a different source. One needs to perform graph aggregation in a wide variety of situations, e. g. , when applying a voting rule (graphs as preference orders), when consolidating conflicting views regarding the relationships between arguments in a debate (graphs as abstract argumentation frameworks), or when computing a consensus between several alternative clusterings of a given dataset (graphs as equivalence relations). Other potential applications include belief merging, data integration, and social network analysis. In this short paper, we review a recently introduced formal framework for graph aggregation that is grounded in social choice theory.
[23] After the deposition of the catalyst layer, conspicuous Fe peaks arise in the overview survey, whereas the Sn 3d signal almost vanishes (Figure  2a ). This observation is reasonable since the iron oxide thickness is in the range of the average XPS analysis depth of 10 nm. 22b,25] The nature of the conductive SnO 2 layer remains unchanged with a marginal Sn 3d and O 1s peak shift to lower binding energies (Figure  2b, c ). Furthermore, both layers are of amorphous nature since the X-ray diffraction (XRD) pattern (Figure  3 ) only features peaks of the crystalline Al template frame (Crystallographic Open Database, COD 9008460) and Au/Ni electrical contact (COD 1100138 and COD  2100649). Since the crystallinity of the individual layers is often crucial for their functional performance,  [15d,22c,26]  thermal treatments are applied to the SnO 2 and Fe 2 O 3 layers with the objective of maximized catalytic turnover in the OER.
50 data points were recorded for wavelengths between 380 and 1050 nm under an angle of 70° for each measurement. The software SpectraRay/3 was used to fit the data orientation (Θ) and ellipticity (ε) with fixed optical models for Fe 2 O 3 and SnO 2. SEM and EDX were carried out on a JEOL JSM 6400 PC implemented with a LaB 6 cathode and SDD X-ray detector. Further SEM images and EDX spectra were recorded with a Zeiss EVO 40 microscope featuring a tungsten cathode and a lithium-drifted silicon detector. For TEM, SnO 2 /Fe 2 O 3 /IrO 2 nanotubes were dissolved in 0. 1 m NaOH and characterized using a JEOL 3010 microscope. The crystal structure was investigated by powder X-ray diffraction measurements using a Bruker D8 Advance diffractometer in reflection mode and with Cu Kα 1 radiation (λ = 1.
20 V relative to the NHE). All electrochemical measurements including cyclic voltammetry, EIS, and steady-state electrolysis were done at room temperature in a 0. 1 m KH 2 PO 4 electrolyte adjusted to pH 7 or 1 m NaOH using a Gamry Reference 600 or Gamry Interface 1000 potentiostat. Cyclic voltammograms were measured at a scan rate of 10 mV s -1. Impedance data were collected between 100 kHz and 0. 05 Hz at +1. 10 V applied potential using 10 mV amplitude perturbation and analyzed with Gamry Echem Analyst in order to generate the fits presented. Steady-state electrolysis measurements were carried out in a potential range of +1. 30 V ≥ E ≥ +0. 90 V (overpotentials 0. 68 ≥ η ≥ 0. 28 V) each for 3 h. The current densities J presented in the main text are mean values of the last hour of electrolysis, averaged over at least three individual electrodes.
Acknowledgements The authors thank  A. Both-Engel  for the XPS measurements. The authors further acknowledge  Prof. W. Peukert  and  P. Hoppe  for the ICP-OES data. This work was funded in part by the project "tubulAir±" (No. 03SF0436G ) supported by the  Bundesministerium für Bildung und Forschung , by the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation program  (Grant Agreement No. 647281 , " Solacylin "), and by  COST Action MP1402 "HERALD", a European cooperation program. M. E. D. is indebted to the  French Ministry of Higher Education, Research and Innovation  for the Ph. D. grant.
Electrical lines Communication lines Figure  1 : The past of the electricity system. One of the greatest inventions of the 20th century. 3 Complexity an overview of the recent research. Table  1  shows the overview of research documents produced since 2010 (excluding 2018) analyzed by different search terms. The search terms have been combined with similar variants within the power systems field to observe results as accurately as possible. We looked for each search term in the abstract, title, and paper's keywords. In addition, we investigate the most cited articles in each search criterion as well as the most noticeable research authors by the number of articles produced. A total of 23,619 documents between 2010 and 2017 are found in the SCOPUS database by using search term "smart grid" OR "smart distribution network" alone in the abstract, title, and keywords and 17,757 if the search term is "renewable generation" OR "renewable energy sources.
The literature has a relevant amount of publications in this field that we selected and revised in this section. Since consideration of uncertainty is crucial for smart grid models  [44] , we investigated in detail this component in the studied models. We also include papers published in 2017 (55 publications appear in the SCOPUS database with the search term "energy resource management" OR "energy scheduling" AND ("uncertainty" OR "uncertain" OR "variability") between 2010 and 2017, of which 22 are from 2017). However, we could observe that the majority of the proposals still lack the consideration of full component uncertainty and/or DR in the model. Table  2  identifies the characteristics of the main publications we selected in what regards the considered energy resources and in terms of uncertainty consideration in the model.
However, many real-world applications may require synergies between methods belonging to the three fields to obtain an acceptable solution. With the evolution of technology in diverse engineering fields, real-world problems are becoming more challenging, limiting the use of exact methods. Due to this, CI has emerged as a powerful tool to provide acceptable solutions in different domains. As a proof in the increasing interest of the research community regarding CI applications, Figure  5  shows the number of publications in the main three topics of CI from 2000 to 2016 (17-year span), obtained after a search in the SCOPUS database  [24]. The search was done putting as a filter the terms shown in Figure  5 , and considering all areas of applications. As a result, 24,706 publications in total were found when searching for "evolutionary computation OR evolutionary algorithms," 23,995 publications using "Artificial Neural Networks," and 49,623 when searching for "Fuzzy systems.
Evolutionary Computation (EC) in the Energy Domain. EC can be applied to problems of all areas of engineering. In this review, however, we are interested in applications related to complex problems in the energy domain. Therefore, in Table  4 , we have grouped the most cited works of the EC paradigm applied to the energy domain in the span 2010-2017. The table is organized from the top 1 cited paper to the top 10 according to the SCOPUS database. We show the specific EC approach used, the problem that was solved, and some characteristics related to the work. In general terms, Table  4  confirms that EC is mainly used to solve optimization problems. Problems such as economic load dispatch (ELD), optimal power flow (OPF), and optimal operation of microgrids are addressed by the most influential works, mainly due to the key role that those problems play in power systems.
Due to the rising needs, several electricity market simulators have been developed, as can be consulted in  [5, [121] [122] [123] [124] , which provide interesting reviews on electricity market simulators. In fact, a total of 2454 documents related to electricity market simulation can be found in the SCOPUS database, until the end of 2017. Such works start emerging slowing from 1981, and several peaks of interest in this theme are well highlighted throughout the years, as can be seen from Figure  7. As can be seen from Figure  7 , there has been a significant increase in the interest in research on electricity market simulation in the beginning of the millennium, with a huge increase in the number of documents published during these few years. In fact, the 10 most cited documents in this area all refer to the first decade of the 2000s, as depicted in Table  8.
Additionally, the simulated market model represents the UK electricity market before its restructuring process of 2001; hence, this model is severely outdated. The Genoa Artificial Power Exchange (GAPEX)  [154]  is an agent-based framework for modeling and simulating power exchanges. GAPEX is implemented in MATLAB and allows the creation of artificial power exchanges reproducing exact market clearing procedures of the most important European power exchanges  [155]. The Electricity Market Complex Adaptive System (EMCAS)  [156]  uses an agentbased approach with agents' strategies based on learning and adaptation. Different agents are used to capture the restructured market heterogeneity, including generation, demand, transmission and distribution companies, independent system operators, consumers, and regulators.
PV-Prosumers4Grid is studying novel self-consumption and aggregation models for prosumers, with the aim of supporting large-scale PV integration in the system. EU-SysFlex aims at achieving an efficient coordinated use of flexibility to enable the wide spread of renewable generation. This requires defining the right amount of flexibility and system services to support transmission system operators. iDistributedPV is developing affordable solutions to increase the penetration of distributed solar PV based on the effective integration of solar PV equipment, including the exploration of several related concepts The significant work being developed in the scope of the multiple projects in the field is resulting in several relevant works in the domain of smart grid and microgrid simulation. In fact, an astonishing number of 15,723 documents are found in the SCOPUS database when searching for Microgrid OR Smart Grid OR Energy Systems Simulation, until the end of 2017.
Acknowledgments The present work has been developed in part under the EUREKA- ITEA2  Project  M2MGrids  ( ITEA-13011 ) and Project  SIMOCE  ( ANI|P2020 17690 ) and has received funding from  FEDER  funds through  COMPETE program  and from national funds through  Fundação para a Ciência e a Tecnologia  under the project  UID/EEA/00760/2013. In addition, it was supported in part by Grant agreement no. 703689  (project  ADAPT ). Additionally, this work has profited from ideas from the proposal of the recently funded project with ref. 02/SAICT/2017/28983  from  CENERGETIC. This work has been also partially supported by  Consejo Nacional de Ciencia y Tecnologia (CONACYT) ,  Mexico.
Tackle Challenges in the New Paradigm of Power Systems 3. 1. 31 Overview and Status of Recent Research. In the last years, research has been devoted to deal with this complexity and overcome the challenges brought by the new paradigm of modern power systems. We have looked at scientific research over the last few years (since 2010) in the SCOPUS database [24]  (i. e. , in December 2017) using different search terms to analyze the number of publications produced and provide.
Rationale and structure of the review The key objective of this paper is to give an overview of low-enthalpy < °( 150 C) geothermal heat available in sedimentary aquifers suitable for direct utilization. An overview of the literature is given in Section 2, where we discuss geothermal energy in sedimentary aquifers, geothermal potential, production, installed capacity, and resource assessments. In Section 3, we present our global assessment of the geothermal resource base for direct heat. To quantify technical and theoretical potential, we apply a volumetric heat-in-place method. We explain how aquifer volume is derived and how associated subsurface temperatures are calculated using global geological and geophysical data sets. We estimate the geothermal potential for generalized direct heat and for common applications including greenhouse heating, spatial heating, and spatial cooling.
Although bulk thermal conductivity can strongly affect geothermal gradients as shown in Fig. 2 , its variability is generally less than surface heat flow and radiogenic heat generation. For our global subsurface temperature model, we assume a fixed bulk thermal conductivity of 2 Wm -1 K -1 as a base case for all aquifers and make use of publically available surface heat flow data (Fig. 6 ). As a starting point, we use the surface heat flow model of Artemieva  [66]. It is an improved interpolation of the original data set from Pollack et al. [67]  and covers most of the continents at a resolution of 5°×5°. For full map coverage, we use the global heat flow model from Davies  [68]  to fill the gaps. Models with higher resolution are used for Europe  [57] and the USA  [69]. We assume higher heat flow values for volcanic regions based on GPS locations from the Global Volcanism Program  [70]  database.