dataesr/scientific-paragraphs-categorization huggingface dataset:
The excitation noise was band limited between 1 Hz and 200 Hz. Datasets of 33 s length were recorded without and with the added mass at the different positions shown in Fig. 4  (right). For processing with the different motion extraction methods, the video frames were separated to 160 ROIs, in total, of size 12 × 37 pixels. The horizontal displacements from each of the ROIs were estimated by the three introduced methods, namely Taylor approximation (Section 3. 1. 2), quadratic surface fitting (QSF, Section 3. 1. 3) and the proposed EX-ST (Section 3. 1. 5) that all share the ZNCC technique (Section 3. 1. 1) as a prior step. The computation time per frame of each algorithm is shown in Table  2 , indicating that EX-ST takes about twice the time than Taylor or QSF.
Evaluation of motion extraction methods in OMA context In this section, the different motion extraction algorithms are evaluated in the context of modal analysis using data from the beam in the reference condition (without added mass), and compared to results from the laser data. First, a direct comparison of  the extracted displacement data to the laser data is made in terms of the root mean squared error. Second, the estimated natural frequencies and damping ratios and their uncertainty bounds obtained with the covariance-driven subspace algorithm are evaluated. Finally, the quality of the mode shape estimates is evaluated for the different methods based on the FE mode shapes.
Direct comparison to laser data Since time synchronization between the laser sensors and the camera was not possible, the laser data was synchronized a posteriori with the image flows by using cross correlation between signals. Furthermore, the extracted displacements from the video were converted from pixels into millimeters by using the pinhole camera model through scaling the distance between two targets in the world coordinate with its pixel distance in the image coordinate. The scaling factor was, thus, estimated to be 1. 007 mm/pixel. In Fig. 6  the motion signals extracted from the vision and laser systems are shown at the upper laser sensor (position 1/1), corresponding to ROI 2 in the motion extraction. The signals are represented on top of each other for comparison. It is observed that the displacements obtained from any of the three motion extraction algorithms seem to match very well with the reference laser data for the whole dataset of 33 s length.
Precision of the natural frequencies and damping ratio estimates The estimated frequencies and damping ratios and their ±2𝜎 confidence intervals, obtained from the vision data with each of the three motion extraction methods as well as the LDS, are stated in Table  4  and visualized in Fig. 8. The confidence intervals are in absolute terms and have the same units as the frequencies and damping ratios, respectively. It can be noted that the first mode has the highest uncertainties, especially its damping ratio. This is due to higher uncertainties in damping estimation in general  [61, 62] , and due to the difficult estimation of this mode in particular, which is at a considerably lower frequency than all other modes while the dataset is relatively short. For all six modes the results show close correspondence although the modal parameter estimates vary slightly.
The confidence intervals obtained from the different datasets overlap, and each of the frequencies and damping ratios is within all the confidence intervals of the other three estimates, showing that the frequency and damping ratio estimates obtained from the three motion extraction methods as well as the LDS are statistically coherent. Moreover, the size of the confidence intervals is similar for the most part for the different methods, with a bit more variation for some of the damping estimates which is naturally to be expected. This shows that the precision of the modal parameter estimates is also similar for the different methods; hence the choice of the motion extraction method does not seem to have a significant influence on the natural frequency and damping ratio estimates.
Application to detect structural changes through added mass Finally, the vision-based technology is evaluated in a monitoring context, where a mass is attached at different positions to the beam (see Fig. 4 , right) to emulate different damages. Based on the chosen EX-ST algorithm, the modal parameters are estimated for each structural state and compared to the reference state. For the modal parameter comparison in the different structural states, a simple approach is adopted from  [52]  based on the natural frequencies and mode shapes together with their uncertainty bounds to infer if changes with respect to the reference are statistically significant. ) be estimated in the mass-free condition, and let the modal parameters ( f𝑖 , φ𝑖 ) with their uncertainties (𝜎 𝑓 𝑖 , 𝛴 𝜑 𝑖 ) be computed from the vision test data under a structural change.
Acknowledgements. This work benefited from  CNRS  and  IGE infrastructures and laboratory platforms. The authors acknowledge the support of the  CASPA program  (Climate-relevant Aerosol Sources and Processes in the Arctic). The authors gratefully acknowledge  Catherine Coulaud  for providing temperature data in Chamonix,  Jean-Luc Jaffrezo  for providing data of previous filter measurements in Chamonix, and  Anthony Lemoine ,  Matthieu Lafaysse  and  Louis Le Toumelin  for providing S2M reanalysis and meteorological data. The authors particularly thanks  Patrick Ginot ,  Anthony Vella ,  Armelle Crouzet , and  Bruno Jourdain  for instrumental and laboratory technical support. Finally, the authors thank  Alexis Lamothe  for assistance during the sampling campaign and  Pete Akers  for his thorough proofreading of the manuscript and his constructive comments.
Financial support. This research has been supported by the  Agence Nationale de la Recherche (ANR)  via contract  ANR-21-CE01-0017 CASPA  and  INSU-CNRS (National Institute of Sciences of the Universe)  via its national  LEFE program  ( Les Enveloppes Fluides  et l'Environnement) and by a grant from  Labex OSUG@2020  (Investissements d'avenir - ANR10 LABX56 ) and  IDEX-UGA   ANR  project  ANR-15-IDEX-02. https://doi. org/10. 5194/egusphere-2023-744Preprint. Discussion started: 28 April 2023 c Author(s)  2023. CC BY 4. 0 License.
MOLA records The MOLA Precision Experimental Data Record (PEDR) dataset features a total of 8505 profiles, acquired in the mapping and extended phases of Mars Global Surveyor (MGS) from February, 1999 to May, 2001, which spanned approximately a full Martian year  [1]. The PEDR dataset was processed using MGS orbit trajectory model and a Mars rotational model by GSFC dating back to 2003. Therefore, we have incorporated a refined orbit model from  [4]  and IAU2015 Mars rotational model  [5]  in the MOLA geolocation reprocessing. Meanwhile, to account for the special relativity effect, the pointing aberration correction has also been taken care of in the reprocessing  [6].
Method This research uses qualitative type and gathered primary data from literature reviews with case studies as the approach method. The qualitative study examines and comprehends the significance of an individual or a group of people concerning a social issue  (Creswell, 2019). This qualitative method with a case study approach was selected since it facilitated exploring the protection of the poor in Cibarani Wewengkon, which had been regulated in Regional Government Regulation No 8 of the Year 2015 on the recognition, protection and preservation of indigenous people. The analysis results were expected to reveal the influencing factors on the poor policy implementation related to the protection of Cibarani Wewengkon The data, we collected secondary data as our main data. The secondary data have been processed previously and are used as supplementary information  (Sugiyono, 2009; Oktaviani et al.
, 2021). The secondary data were gathered through numerous sources, such as research articles and books relevant to customary rights, along with the documents of regulations for Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktik dalam Bidang Pendidikan dan Ilmu Geografi 28(1), 2023, 96-106 99 customary rights protection, mass media reporting the issues in Cibarani Wewengkon, and other relevant secondary data sources. The obtained data were later analyzed using the interactive model. The analysis was carried out using direct, interactive, and sustainable qualitative data analysis to generate reliable and recent data. The first data analysis activity was data reduction, where we sorted the primary data, focused the data, and looked for the data themes and patterns in a secondary manner. Secondly, we presented the data obtained from the data reduction in the form of descriptions, charts, and others.
unctad. org). For instance, with a low score in masculinity, compared to Pakistani managers, South Korean managers are expected to place greater emphasis on consensus, equality and quality of work life, and therefore incentives like free time and flexibility are preferred (hofstede-insights. com). This may have implications for how personal resources, such as psychological empowerment, may influence employees' creative performance. Highlighting any cross-cultural variations is likely to advance creativity literature as systematic comparative studies between developing and developed countries, especially from countries outside of the USA and Europe, are scarce  (Brough et al. 2013; Guo et al. , 2018). In the Pakistani sample, data were collected from medical representatives in one multinational firm in Pakistan.
Among the ten anatomy departments in Greece today, only the two Departments in Athens (National and Kapodistrian University of Athens -NKUA) and Thessaloniki (Aristotle University of Thessaloniki -AUTh) have well-organised cadaver donation programmes. At the same time, the other universities train their students in anatomy by using prosected or formalin-embalmed or fresh frozen cadaveric specimens derived from imports from other countries. The AUTh also receives unclaimed cadavers after a special royal decree that allows the co-capital to receive such corpses for dissection. The NKUA uses exclusively donated corpses. The following data are derived from the collaboration between the two Anatomy Departments of the Medical Schools of the NKUA and the AUTh on the procurement of cadavers based on the body donation programmes and the sources of cadavers before the body donation period.
Background: Optimal consolidation for young patilents with relapsed/refractory (R/R) follicular lymphoma (FL) remains uncertain in the rituximab era, with an unclear benefit of autologous stem cell transplantation (ASCT). The multicenter, randomized, phase III FLAZ12 (NCT01827605) trial compared anti-CD20 radioimmunotherapy (RIT) with ASCT as consolidation after chemoimmunotherapy, both followed by rituximab maintenance. Patients and methods: Patients (age 18-65 years) with R/R FL and without significant comorbidities were enrolled and treated with three courses of conventional, investigator-chosen chemoimmunotherapies. Those experiencing at least a partial response were randomized 1 : 1 to ASCT or RIT before CD34þ collection, and all received postconsolidation rituximab maintenance. Progression-free survival (PFS) was the primary endpoint.
14  To increase the complete remission (CR) rate and disease-free survival after salvage treatment, several guidelines still suggest consolidation with high-dose chemotherapy and autologous stem cell transplantation (ASCT). 15  This guidance is based mainly on the results of the CUP trial, which was conducted in the pre-rituximab era. 16  No compelling evidence of an ASCT benefit is available in the context of modern chemoimmunotherapy, particularly when followed by rituximab maintenance,  17  although some retrospective evidence suggests a potential advantage. 18  Radioimmunotherapy is an active agent in R/R FL. 19  As consolidation, it has been investigated after CHOP at diagnosis but is often used in the R/R setting as a less toxic consolidation regimen than ASCT. 20, 21  To address some of these unresolved issues, the Fondazione Italiana Linfomi (FIL) designed and conducted the randomized phase III FIL FLAZ-12 trial (ClinicalTrials.
ACKNOWLEDGEMENTS We are grateful to the  Fondazione Italiana Linfomi  personnel for the management of the study, particularly  Sonia Perticone ,  Marina Cesaretti ,  Antonella Ferranti , and  Maria Vittoria Sacchi. We wish to acknowledge  Giulia Limberti ,  Paolo Rivela ,  Claudia Bertassello ,  Antonella Sofia , and  Noemi Schiena  for data management. This work was supported by  Fondazione Italiana Linfomi  and by a competitive grant from  AIFA  (Cod. :  FARM9RCP52 ). Further support was derived from  Progetto di Ricerca Sanitaria Finalizzata 2021  ( RF-2021-12371972 ) and  AIL AL-ASTI ODV.
In order to cover continuously the entire frequency range from ∼DC up to 10 kHz, four data streams are provided simultaneously at different sampling frequencies: F 3 = 16 Hz, F 2 = 256 Hz, F 1 = 4096 Hz, and F 0 = 24 576 Hz. A detailed and comprehensive description of LFR measurements capabilities and data processing can be found in  Chust et al. (2021) ,  Maksimovic et al. (2020). Throughout the day of VGAM1, the RPW instrument suite operated in BURST mode. The LFR recorded continuous waveforms (CWFs) sampled at F 2 , compressed spectral matrices (BP2) every 5 s, and synthetic wave parameter sets (BP1) every 1 s. These basic wave parameters, BP2 and BP1, were both calculated regularly on board from the F1 and F0 data streams, completing the frequency range up to 10 kHz. TDS was operating in a higher cadence mode with a regular waveform snapshot taken every 10 s at the rate of 262 ksps and the length of 32 ms between 06:00 and 18:00 UT.
Additional investigations of the statistical occurrence of these waves and their role in the energy transport and dissipation will be done in future studies. Moreover, the next Venus flybys of Solar Orbiter will allow complementary analysis regarding the nature of the waves and the plasma properties in the induced magnetosphere of Venus. RCA is supported under NASA contract NNN06AA01C and thanks NASA headquarters and the NASA/GSFC Solar Orbiter project office for their continuing support. Solar Orbiter is a space mission of international collaboration between ESA and NASA, operated by ESA. This work is supported by the Swedish National Space Agency grant 20/136. Solar Orbiter magnetometer operations are funded by the UK Space Agency (grant ST/T001062/1). Tim Horbury is supported by STFC grant ST/S000364/1.
The proliferation of unmanned aerial vehicles (UAVs) opens up new opportunities for on-demand service provisioning anywhere and anytime, but also exposes UAVs to a variety of cyber threats. Low/medium interaction honeypots offer a promising lightweight defense for actively protecting mobile Internet of things, particularly UAV networks. While previous research has primarily focused on honeypot system design and attack pattern recognition, the incentive issue for motivating UAV's participation (e. g. , sharing trapped attack data in honeypots) to collaboratively resist distributed and sophisticated attacks remains unexplored. This paper proposes a novel gametheoretical collaborative defense approach to address optimal, fair, and feasible incentive design, in the presence of network dynamics and UAVs' multi-dimensional private information (e.
A. Simulation Setup We consider a simulation area of 200 × 200 × 20 m 3 with one GCS and I = 10 uniformly distributed Parrot AR Drone 2. 0 UAVs. Each UAV is embedded with a honeypot system and communicates with the GCS and other UAVs via Wi-Fi communications. Similar to the project HoneyDrone  [14] , the honeypot reads UAV profiles from the configuration file to emulate UAV's radio interfaces and offers low to medium interactions with adversaries for Wi-Fi protocols. The Telnet attack  [14]  is considered in the simulation, and the honeypot's captured VDD (including IP address, port number, connection type, commands, and timestamps of attackers) is recorded into a local MongoDB database. The GCS requests VDD from UAVs every 6 seconds, with a maximum communication delay of 2 seconds and a default system budget Ω = 460.
The Normal Distribution Transform Occupancy Map (NDT OM) is a mapping algorithm able to represent a dynamic 3D environment. The resulting map has fixed boundaries, thus a robot with unbounded displacement might fall outside of the map due to memory limitation. In this paper, a recentering algorithm called NDT RC is proposed to avoid this issue. NDT RC extends the use of NDT OM for vehicles with unbounded displacements. NDT RC provides a seamless translation of the map as the robot gets far from the center of the previous map. The influence of NDT RC on the precision of the estimated trajectory of the robot, or odometry, is examined on two publicly available datasets, the KITTI and Ford datasets. An analysis of the sensitivity of the NDT RC to its tuning parameters is carried out using the Ford dataset, while the KITTI dataset is used to measure the influence of the density of the input point cloud.
The results show that the proposed recentering strategy improves the accuracy of the odometry calculated by registering the latest lidar scan on the generated map compared to other NDT based approaches (NDT OM, NDT OM Fusion, SE-NDT). In particular, the proposed method, which does not perform loop closure, reduces the mean absolute translation error by 16 % and the runtime by 88 % compared to the NDT OM Fusion on the Ford dataset.
This method projects the 3D laser scan into 2D and computes normals, making it more difficult to use with LiDARs exhibiting non regular patterns (e. g. , livox avia). It should be noted that although the method runs in real time, it leverages the rendering pipeline of a GPU, making it more costly to implement on hardware limited to a CPU. It is also possible to perform the odometry computation separately from the map and obstacles representation. The current most precise method on the KITTI odometry dataset  [18]  using Laser data only is LOAM (LiDAR Odometry And Mapping)  [19] ,  [20]. It divides the mapping task in two: a coarse odometry step running at the sensor speed, and a slower matching and registration step. This method uses 3D features, corners and surfaces, to register scans together.
The large scale datasets used are the Ford Campus Vision and Lidar Data Set  [21]  (Ford dataset) and the KITTI odometry dataset  [18]. Second, an analysis of the sensitivity of this algorithm to its tuning parameters and the density of the lidar is carried out. The NDT RC, similar to the NDT OM, depends on several parameters, and to the best of the authors knowledge, the influence of those parameters on the precision of the odometry has not been evaluated. The NDT RC algorithm has been used in OAST  [22] , an algorithm for obstacle avoidance during teleoperation of UAVs. This paper focuses on the mapping algorithm, while the aforementioned paper presents the obstacle avoidance algorithm. The theory behind NDT OM is described in Section II, then NDT RC is described in Section III. NDT RC is tested on two publicly available datasets in Section IV and the influence of its tuning parameters and of the density of the LIDAR is examined in Section V.
IV. VERIFICATION OF NDT RC In this section, the odometry produced by the NDT RC algorithm is tested on two publicly available datasets: the Ford Campus Vision and Lidar Data Set  [21]  and the KITTI odometry dataset  [18]. The Ford dataset is chosen as the competitor technique NDT OM  [2]  was already evaluated  on it with a fusion mechanism to allow the robot to have a greater movement range  [12]. The KITTI dataset  [18]  has been chosen because it is popular, allowing our results to be compared to other methods. Both datasets are acquired outdoors using a car. The Ford dataset was acquired in urban conditions, while the KITTI dataset contains 11 sequences acquired in various conditions. The LIDAR sensor used is a Velodyne HDL-64E, with a range of 120 m and a rotation rate of 10 Hz. The odometry from the D2D NDT  [25]  is shown as a baseline.
The D2D NDT is tuned by making the parameters vary on a grid, similarly to our algorithm. However, the best parameters for D2D NDT are chosen for each dataset, whereas our algorithm uses a single set of parameters for the two datasets. Moreover, to guarantee a fairness of evaluation, we ensured that the results of D2D NDT were at least as good as existing publications applying D2D NDT to those datasets when available  [11]. It is important to note that since our algorithm and the D2D NDT are different, using the same parameters would be unfair, which is why they were tuned separately. Our testing indeed shows  [26]  that the optimal set of parameters for each algorithm are different, thus we have elected to evaluate each of them on the parameters giving the best results and not on the same parameters.
The parameters used for the NDT RC are presented in Table  I. They are selected in accordance with the results of the sensitivity analysis in Section V. Note that the results reported on both the KITTI and Ford datasets are obtained with those same parameters. The size of the map allows a whole LIDAR scan to fit inside the map when the vehicle is at the centre. Moreover, the recentering algorithm is called when the vehicle is further than 10 m from the centre. A study of those parameters is proposed in Section V, where the influence of each of them over the precision and runtime can be seen. The initial guess for initializing the D2D matching process  [9]  between the current NDT map and the NDT built from the incoming point cloud is the last inter frame odometry resulting from a successful match.
A. Evaluation on the Ford dataset The main error metric on this dataset is the absolute trajectory error  [27]  (ATE) per frame. The ATE is obtained after aligning the odometry trajectory obtained using the registration of maps created by NDT RC and the ground truth trajectory  [27] , and measures the absolute error in translation. Different ATE statistics are shown in Table  II. The runtime averaged over the whole sequence is detailed in Table  III. The time needed by the recentering algorithm is negligible (< 0. 5 %) compared to the total time. In the rest of this section, the NDT RC algorithm is compared to other algorithms on the Ford dataset. The NDT RC is compared to the D2D NDT  [25]  as implemented on the Github repository of the authors  1. The following parameters are used for the D2D NDT: a single 3D matching, a resolution of 1.
The fact that NDT RC, which discards the cells that move out of the boundaries of the map results, achieves a   [25]  10. 8 11. 65 263 NDT OM Fusion  [12]  1. 7 -<2000 SLAM method  [28]  -4. 48 <300 1 with 1. 5 m cell size. more precise odometry compared to NDT OM Fusion, which keeps all the cells, can appear surprising. This improvement is considered to be partly due to the loop closure issue mentioned in the work of Stoyanov, Saarinen, Andreasson, et al. [12]. Indeed, keeping all the cells mean that any drift in odometry will make the matching more difficult for NDT OM Fusion in case of loop closure. NDT RC does not have this problem since it does not keep the cells outside the boundaries of the map. A SLAM method based on the extraction of planar segments from the LIDAR data is proposed by Lenac, Kitanov, Cupec, et al.
[28]. The authors report the RMSE on this dataset. The RMSE for their method is 4. 48 m. The mean runtime reported are around 250 ms for point cloud segmentation, 1. 5 ms for relative pose computation, and less than 50 ms for the global map update. However, because this is a SLAM system, the global map runtime can increase with time. A spike in runtime of more than 600 ms can be seen at the end of the trajectory (Figure 33  [28] ). NDT RC has a lower RMSE of 1. 49 m, and a faster runtime of 229 ms. This comparison is interesting because it shows that a lower error is obtained with NDT RC despite the absence of loop closure mechanism. Those results are summarized as well in Table  IV.