dataesr/scientific-paragraphs-categorization huggingface dataset:
A value of C = 2 15 was also tried and it was concluded that higher values reduced the performance by over-fitting the training dataset. In addition, it was found that models trained with higher values of C are computationally expensive to train. Therefore, from results, a value of 2 5 was selected for C. After setting the value of C to 2 5 , various values of ǫ were tried to find its optimal value. From the results, it was found that smaller values of ǫ did not have a significant influence on the performance on SVR model. The performance significantly reduced for values larger than 4. From results, a value of 2 was chosen for ǫ. Tables  5  and 6  show the results of different experiments for select C and ǫ.
ET Hyper-Parametric Tuning For Extra trees algorithm, number of trees (M), number of samples required for splitting a node (n min ) and attribute selection strength parameter (K) are the three important hyper-parameters. The parameter K represents the size of the random subsets of features to consider when splitting a node, and can be selected in the range  [1,. , n] , where n is the total number of features. The total number of trees in the forest is represented by M; for our case, we fixed M to 1000 trees. Larger values of smoothing parameter (n min ) would result in smaller trees, higher bias and smaller variance  [48]. For hyper-parameter tuning, this parameter was varied in the range  [2,. , 10]  to investigate its influence on model's accuracy. From results, it was found that changing n min did not yield a significant accuracy improvement on the hotel's HVAC energy consumption dataset.
The performance started to deteriorate for d max greater than 10. The trees with d max = 1 resulted in higher values of RMSE, MAE and MSE, and lower value of R 2. From these results, it is clear that, on the studied dataset, extremely randomized trees' performance was more influenced by parameter d max instead of n min and K. This may vary from dataset to dataset; however, for most of the cases, default values of the parameters may result in acceptable performance. Table  7 -9 show the results of various experiments for selecting ET hyper-parameters.
Comparison and Discussion Predictive performance of SVR, ET and DHN models are nearly comparable. Figure  4  illustrates the plot of actual hourly HVAC energy consumption vs. predicted energy consumption by the ET model. Models' ability to accurately predict energy consumption is clearly illustrated by the level of linear relationship between predicted and measured values in Figure  4b. The figure shows the strong nonlinear mapping generalisation capabilities of the model, and it can be effectively used as prediction models for decision-making processes. Table  10  shows a comparison of models' performance for both training and testing datasets. According to the results, DHN performed marginally better as compared to the other two developed models. For all three models, the R 2 value is higher than 0.
84 and RMSE values were in the range of 3. 08 and 4. 28 for both training and testing datasets. From these results, it can be concluded that the developed models have the capabilities to accurately predict the hourly HVAC energy consumption. From Table  10 , it is demonstrated that all developed models have nearly comparable performances and could be equally used to accurately predict the hourly HVAC energy consumption. It was expected that the prediction accuracy will be significantly enhanced by using a deep learning algorithm due to the 'deep' property of the network. However, this was not the case, as DHN performed marginally better than the other two ML algorithms. From tuning the hyper-parameters of DHN, it was found that the network complexity (i. e. , increasing network's number of layers, neurons and previous hours values of input variables) did not significantly improve the performance of the model.
Median values of all models closely match with the actual data. The "tailedness" and "asymmetry" of the probability distribution of a real-valued random variable is measured by Skewness and Kurtosis. It was found that DHN model has slightly lower Kurtosis value as compared to the other models and actual dataset. Minimum and maximum values are used to identify outliers in the dataset, it was found that ET has comparatively higher minimum value as compared to the actual dataset. The results also show that all models have under predicted some of the higher values of HVAC energy consumption. This might be due to the fact that those values were under-represented in the training dataset. Figure  5  shows the violin plot for probability distribution for extremely randomized model during different hours of the testing dataset.
Funding: The work was carried out in the framework of the  FP7  project (Grant No. 609154 ) PERFORMER "Portable, Exhaustive, Reliable, Flexible and Optimized approach to Monitoring and Evaluation of building energy performance" and  Horizon 2020  project (Grant No. 731125 ) PENTAGON "Unlocking European grid local flexibility through augmented energy conversion capabilities at district-level". The authors acknowledge the financial support from the  European Commission.
2013). We then compared them to the nearly-complete mitogenome of Thalassarche melanophris  (Gibb et al. 2007 ) (AY158677. 2) using Blast (MegaBLAST, nr database, E-value threshold: 10, identity threshold 85%)  (Altschul et al. 1990 ). Due to the presence of several stop-codons in the resulting contigs, we polished our Canu assembly using 100bp Illumina HiSeq 2500 reads previously obtained as a by-product of a separate, targeted enrichment project  (Welch et al. in prep)  on a separate individual from the same population (National Museum of Natural History, Smithsonian Institution, voucher: USNM 620721). The reads were aligned with the contigs using BWA  (Li 2013) , and then polished with Pilon  (Walker et al. 2014). Illumina reads were mapped again on the resulting assembly sequence and drops in coverage were observed at some positions.
This means that no MinION read covered the entire mitochondrial genome if the RR was not present. Moreover, no significant BLAST match was found for this region (MegaBLAST & BLASTn, nr database, E-value threshold: 10, identity threshold 85%). Therefore, two hypotheses may explain the presence of this repeated sequence: (i) the RR is biologically present in the mitochondrial genome of this individual of Puffinus lherminieri, and potentially in other species of Procellariiformes, but was never sequenced until now. The large number of repetitions implied that MinION sequencing was difficult and led to differences among reads. Illumina sequencing was difficult in this region due to the high AT content and so, no Illumina read linked the RR to the rest of the mitogenome. Alternatively, (ii) the RR may be an artefact, due for example to chimeric amplification in the early stages of the PCR, containing parts of the mitochondrial genome and a nuclear sequence not catalogued on Genbank.
Acknowledgements We thank the  University of La Rochelle (ULR)  for financial support, and the  ULR molecular core facility  for lab support. We thank  Helen James  and the  National Museum of Natural History, Smithsonian Institution , for access to tissue sample USNM 620721; UCE data for this individual was originally gathered for an unpublished phylogenetics study of Procellariiformes conducted by  AJW ,  RTC ,  Helen James , and VB. We are grateful to the  bioinformatics platform Toulouse Midi-Pyrenees (Bioinfo GenoToul ) for providing help and computing. We also thank  C. Precheur , the  Parc Naturel Regional de la Martinique  and the  DEAL Martinique  for help and funding of the research program on the shearwater. Salary of LT is covered by a grant from the  University of La Rochelle.
2 Sequence Average coverage Minimum coverage Maximum coverage Ct1 3 189 433 5 927 Ct2 3 523 433 9 067 Ct1 first part 560 433 683 Ct2 first part 560 433 683 Ct1 second Ct2 second part 5 919 4 229 9 067 RR Ct2 without 1 547 574 4 554 part 4 945 3 812 5 927 RR Ct1 without 1 395 465 2 449 RR in Ct2 40 0 745 RR in Ct1 575 0 6 971 Ct2 1 386 0 4 554 Ct1 1 327 0 6 971 coverage coverage coverage Average Minimum Maximum Figures Tab. 3 Sequence Figure 1. O bject of the study CR nearly complete mitogenome CR % of covered 100 100 100 100 100 100 100 100 12 41 93 95 bases bases % of covered Genbank accession number AP009193. 1 42,11 42. 8 40,70 42. 7 43,36 42. 7 43,36 32. 3 42,66 42. 7 41,76 41. 8 % of GC % of GC Sequencing method PCR and Sanger-sequencing PCR, primer-walking and shotgun sequencing PCR and Sanger sequencing Study Rains et al.
Limits and uncertainty of species detection Using the 127-base pair (bp) cytochrome c oxidase subunit I (COI) fragment, we did not find an unequivocal correspondence between molecular operational taxonomic units (MOTUs) and species because some MOTUs had 100% sequence identity matches with multiple species in the Barcode of Life Data System (BOLD) database  (32). This issue mainly concerns the Carcharhinus genus, which is recognized as taxonomically problematic and polyphyletic  (33). Therefore, although 16 different shark MOTUs were identified, we opted for the conservative approach of merging MOTUs to present the minimum species richness (13 species). With a trade-off between primer universality and taxonomic resolution (  16 ), the imperfect nature of currently available metabarcoding primers introduces a degree of uncertainty regarding the identification of certain species  (34).
It is thus very likely that increasing the eDNA sampling effort would detect them in New Caledonia because the rarefaction curves show that eDNA can outperform the other methods in terms of species detectability  (12) , but additional work on refining the design of primers is needed to cement eDNA as a standard tool for the study of dark diversity of sharks. There are also important caveats associated with eDNA detection, and traditional survey methods still have a number of advantages over Table  1. Models fitted for species rarefaction curves obtained from UVC, BRUVS, and eDNA using the nls function in the stats package and the AICc for small sample bias (package AICmodavg). The best-fitting model for each sampling technique is in bold, whereas the overall best-fitting model (all three techniques) is underlined.
Bioinformatics analyses The bioinformatic analysis was based on an OBITools metabarcoding software suite  (50). The pipeline used for data analysis is summarized in table  S2. Quality of the reads was assessed using FastQC. Paired-end reads were aligned using illuminapairedend, and alignments with quality scores >40 were kept. The aligned data set was demultiplexed using ngsfilter. A length filter (obigrep) was applied to the aligned reads (120 to 135 bp), and reads containing ambiguous bases were removed. The reads were then dereplicated using obiuniq, and a chimera removal step.
Acknowledgments: We thank the crew of the research vessels  Amborella  ( Government of New Caledonia ),  Alis Institute of Research for Development, and Plan B (Waitt Institute)  for their help with data collection during oceanographic campaigns. We thank  G. Mou-Tham  and many others for UVC collection and BRUVS analyses. We would also like to thank  M. Dando  for the scientific drawings used in the manuscript. Funding: This work is an outcome of the Pristine, APEX and e(lasmo)DNA projects co-funded by the  Total Foundation , the  Pew Charitable Trusts , the  Government of New Caledonia , and the  University of Salford  R&E strategy funding. Author contributions: G. B. ,  S. Mariani ,  D. M. , and L. V. designed the study with inputs from all coauthors. J. B. , O. S. W. , and  S. Mariani  designed and carried out the eDNA laboratory procedures and bioinformatics pipeline.
This algorithm solves the problem of finding the shortest path (a path of minimum length) from a vertex to vertex z in weighted graph, the weight is a positive number so cannot be passed by the negative node, but if so, then the solution given is infinite. Dijkstra's algorithm has a straightforward nature. In keeping with the meaning of greed which is literally greedy or greedy, but not in a negative context, the Greedy Algorithm is concerned only with the best solution to be taken at every step without thinking of future consequences  [11]. Eclipse is an IDE (Integrated Development Environment) to develop software and can run on all platforms (platformindependent). Here is the nature of Eclipse  [15]. Spring-boot is a java framework that is a compilation of some Spring Framework element libraries  [8].
Hibernate is a Framework for Object Relation Mapping (ORM) which in hibernate maps objects into the database  [7]. Conceptual data model is a concept related to the user's view of the data stored in the database  [1] , to manage database we can use MySQL Workbench is a visual application that is used to manage database  [16] , MySQL is one type of database server that is very popular and widely used to build web applications that use the database as a source and data processing  [5]. Android provides an open platform for developers to create their apps. areas dedicated to the display of notifications, communication of device status, and device navigation  [3]. Framework is a collection of libraries organized in an architectural design to provide speed, accuracy, convenience and consistency in the application development of the definition.
Business Analysis Process Broadcast Position Application In the Figure  3  below explain the business process of the application: the begin from anggota lain searc for data lokasi, they will fill the form application and will be save in database as the Here is a Figure  4  of the implementation login page, user who are register to the group travel can use this login form, for make sure the user group. For Figure  5  group details, it's use for see the details of their group, and in this Figure  5  we can look of our team in one group connection.
Radial Basis Functions (RBF) constitute its mathematical background. They are real-valued functions, taken from the Approximation Theory. Some basic concepts about RBF are given in the next section. Mesh morphing based on RBF proved to give excellent results in many practical examples  (Biancolini and Cella (2010) ,  Biancolini and Groth (2014) ,  Cella et al. (2017) ). Its major drawback is that, despite its meshless working principle, element topology does not change during the morph operation. This last foresees a simple displacement of node locations and the extent of morph must take into account degeneration of mesh quality. The activities presented in this work were financially supported by the RBF4CRACKS project funded by the University of Rome "Tor Vergata" under the program "Consolidate the Foundations".
Conclusions In the present work an assessment of mesh morphing for fracture mechanics is presented. Chosen strategy of morphing is the one adopted by the tool RBFMorph TM , relying on RBF. ANSYS ® Workbench TM is the framework of investigation. A baseline cracked mesh is morphed to supply a multiplicity of different crack geometries. The same geometries are obtained from scratch, using the Fracture Tool embedded in the ANSYS software. A preliminary comparison showed that fracture analyses conducted on morphed meshes are as reliable as conventional ones, which are performed on mesh obtained from the scratch. Next the limits of applicability of the proposed methodology were investigated by performing a parametric analysis in which different crack shapes were obtained by varying both the crack dimensions and aspect ratios.
Therefore this study fills a gap in the literature. Without assuming cultural determination, we do show significant differences between institutions. We present in this section a study that investigates these issues, the methodology of data acquisition, the main themes that the study investigates, and the main results. In order to evaluate students' perceptions of mathematics we elaborated an online survey spread out over all participant countries (Armenia, France, Finland, Georgia and Russia). The survey was elaborated to investigate the three main dimensions of the mathematical courses: • The usefulness of mathematics. • Mathematical courses in engineering courses-Contents and Methods. • Perception of Mathematics. The survey was spread with a web tool and translated into each partner language to ensure that the meaning of the questions was adequately taken into account.
A total of 35 questions were answered by 1548 students from all participant countries. After collecting the data from the online survey we used the statistical package R to analyse the data and draw conclusions. We performed a Principal Component Analysis to verify whether there were some patterns in the students' responses. Using the graphical representation of data, we can propose the hypothesis that the methodology of teaching mathematics of each country shapes the average students' perception towards mathematics. Thus, the first conclusion of this analysis is that in the European universities the mathematics are taught as tools to solve problems, that is, mathematics by practicing, while in the non-European universities, the mathematics are taught focussing on proofs and theorems, that is, mathematics by thinking.
SEFI makes recommendations on assessing students knowledge and on the use of technology. Here it is also emphasized that learning should be meaningful from the students' perspective. Students' perceptions on mathematics in each of the universities were investigated and results were presented in Chap. 1, Sect. 1. 3. The SEFI framework and related EU-pedagogy was described in Chap. 1, Sect. 1. 1. To make a comparison of curricula and courses, a methodology was created. This methodology was described in detail in Chap. 2. Comprehensive information on partner countries' curricula, courses and instruction was collected and organized in the form of a database. For comparison similar data was collected from participating EU-universities, Tampere University of Technology (TUT), Finland and university of Lyon (UBCL), France.
The final δ 18 O values for each sample is the average of two replicates, yielding a reproducibility of better than ± 0. 2 ‰ (1s). The age-depth model of PET09P2  (Brisset et al. , 2013)  was constructed using the R package Clam  (Blauuw et al. , 2011). For the purpose of this study, we have recalculated the age-depth model using the Bacon R package  (Blaauw and Christen, 2011)  and implemented the function "proxy. ghost" (square resolution:200) in order to take into account the 10 chronological uncertainties associated with the proxy representation. The result is a range of possible ages for each sample depth, each of which is represented on the graph. The darkest grey is assigned to the most likely value within the entire core (normalised to 1). Lower age probabilities are coloured in lighter grey.
, 1997). Other detrital or flood events have been recorded between 4500 and 3000 cal. BP in the Alps for 20 example at Bourget Lake  (Arnaud et al. , 2005; 2012)  and a review of dated-landslides revealed a cluster around 4200 cal. BP supporting the presence of heavy precipitation  (Zerathe et al. , 2014; Fig. 5 ). In the Massif du Mont Blanc (46° N) a moraine contemporary with the 4. 2 kyrs climatic event has been dated suggesting a glacier advance during this period (Le  Roy et al. , 2017). At a broader scale, stable isotope and trace element data from a calcite flowstone located in northern Italy (Buca della Renella; 44° N) have shown that the 4. 2 kyrs event was expressed in mid-latitude Europe by dry climatic conditions 25  (Drysdale et al. , 2006)  (Fig. 5 ). A similar trend has been found at Preola Lake (37° N) in Sicily  (Magny et al.
9 Acknowledgements This work was supported by the  ECCOREV research federation (HOMERE program  led by  F. Guiter  and  C. Paillès ). The PhD thesis work of  R. Cartier  ( Aix-Marseille University ) was funded by the  French Ministry of Education. 5 We thank  C. Vallet-Coulomb  ( CEREGE, France ) for the oxygen isotope analysis of modern Petit Lake waters and  P. Chaurand  ( CEREGE, France ) for providing help with the micro-XRF measurements. Thanks to  A. Tonetto  ( Aix-Marseille University ) for managing the  SEM in Marseille. Coring of Petit Lake  (in 2009 and 2012) was made possible thanks to  F. Arnaud  (EDYTEM),  C. Giguet-Covex  (EDYTEM),  E. Malet  (EDYTEM),  J. Pansu  ( Princeton University ), J. Poulenard (EDYTEM) and  B. Wilhelm  (LTHE). 10.
Implementation The presented algorithm was implemented by the application software called AVERPOIN, which is written in MATLAB language. This application can be executed by MATLAB and Octave and is free software provided under the GNU Lesser General Public License version 3 (https://github. com/rrcarrillo/ AVERPOIN). This functional implementation of the presented algorithm is provided as proof of concept. This implementation is not optimized in terms of computational load. Future research to improve the algorithm itself by adopting more efficient methods  (De Loera et al. , 2012)  is advisable. The computational load generated by the integration of the squared l 2 norm of the residual vector over the polytopes is expected to be significantly reduced.
Analytical Solution, Proof of Concept We present several 3-state-and-4-input-neuron matrix examples to further illustrate the functionality of the algorithm. The software AVERPOIN facilitated the analytical calculation of a floating-point number (Ir(C)) that indicated the suitability of each input matrix to generate any output set. The graphical representation helped us to better associate the resulting number, given by the algorithm, and the goodness of each matrix as input-state representation (Figure  7 ). In the case of 3state representations (m = 3), the maximal value of Ir(C) is 1, therefore, Ir(C)=IrN(C). For each matrix, we show the polyhedrons into which the output space was partitioned for the integration process. The input matrices selected as an example cover a range of input representations from worst (A) to best-case scenario (I) showing a gradual decrease in the representation goodness.
FUNDING This research was supported by the  European Union  ( H2020-MSCA-IF-2014 658479 SpikeControl  and  HBP-SGA2 H2020-RIA. 785907 (ER) ),  Spanish MINECO  ( TIN2016-81041 -R partially funded by  FEDER  and  IJCI-2016-27385 ), Program 9 of the 2015 research plan of the  University of Granada  (project  ID   16 ), and the  GENIL  grant  PYR-2014-6  from  CEI BioTic Granada.
Different algorithms are used to calculate solar irradiance on horizontal and vertical surfaces of the 3D city models. The goal of this paper is to evaluate the hourly solar irradiance calculated by two widely used algorithms in order to assess photovoltaic (PV) potential of the 3D city models. Both algorithms are implemented in an open source software infrastructure consisting of PostgreSQL database connected with PostGIS, Python, etc. The results show a significant variation of solar irradiances on horizontal, vertical and tilted surfaces. Finally, the justification of a particular algorithm to assess citywide PV potentials is made.
Data The hourly weather data on wind speed, temperature and horizontal radiation are collected from the Meteonorm software in TMY3 format  (Wilcox and Marion, 2008). The 3D city model of the CityGML format having Level of Detail 2 (LoD2 includes appropriate roof structure) of the city of Karlsruhe is also gathered. A detailed description of the CityGML data format and different LoDs is given in (OGC, 2012).